Resources Catalog
A curated collection of data science resources for R, Python, and beyond.
Overview
This project turns a plain-text resource list into a searchable front end for curated data science references across R, Python, statistics, visualization, research workflows, and life sciences.
It is intentionally both a curation project and a small product-engineering exercise: define a lightweight schema, keep the source easy to edit, and ship a fast browsing experience without introducing a heavyweight backend.
What This Project Includes
- A hand-curated catalog stored in
data/resources.txt, with each entry typed, categorized, and optionally annotated with a short description - A Quarto + R generation layer that builds the filter controls, cards, counters, and pagination from a single source of truth
- Lightweight client-side search and filtering for language, topic, type, layout, and sort order
- A low-friction contribution workflow based on small YAML blocks and documented pull requests
I finally have the feeling that I’m a decent programmer, so I thought it would be fun to write some advice with the idea of “what would have gotten me to this point faster?” I’m not claiming this is great advice for everyone, just that it would have been good advice for me. If you (or your team) are
How to win the war for the soul of the internet, and build the Web We Want.
A tutorial on how to create AI music videos using the text-to-image model Stable Diffusion.
The full breakdown of what a job search in AI with a new Ph.D. looks like.
A look at the Naive Bayes classifier and SVM algorithms. Learn about the Naive Bayes and SVM implementation in Python on a SMS Spam dataset.
While much of the writing and literature on deep learning concerns computer vision and natural language processing (NLP), audio analysis—a field that includes automatic speech recognition (ASR), digital signal processing, and music classification, tagging, and generation—is a growing subdomain of de
Introduction For creating a production deployment of a {shiny} application it is often useful to be able to provide a Docker image that contains all the dependencies for that application. Here we explore how one might go about automating the creation of a Dockerfile that will allow us to build such
usethis::use_github_action(\"check-release\") Hi! This is the first blog post in the “GitHub Action” Series.
Make your results show up beautifully with these packages to make tables in R.
We’ve done it folks! Over 300 free R programming books are now available at www.BigBookofR.com. Of the 343 entries available, 20 are paid products and the rest are all 100% free. Thanks to all the authors, contributors, users readers and cheerleaders who are helping build a rich ecosystem of materia
In this article I’ll teach you how to build a text classification app from scratch. You’ll enter some text from a language, and the app will identify which l...
Vous utilisez Claude Code comme moi pour bosser plus vite sur vos projets de dev ? Hé bien j'espère que vous n'avez jamais eu la mauvaise surprise de voir ...
This article is a curated list of the best open-source Computer Vision projects, heavily based on GitHub's trends in 2024 .
R Markdown is a reproducible authoring format supporting dozens of static and dynamic output formats. Let's review why and how you should containerize Rmd files.
R Markdown is a reproducible authoring format supporting dozens of static and dynamic output formats. Let's review why and how you should containerize Rmd files.
How to set up a minimal (but pretty) website in the modern era.
This document contains a collection of various Shiny tricks that I commonly use or that I know many people ask about. Each link contains a complete functional Shiny app that demonstrates how to perform a non trivial task in Shiny. The complete up-to-date list of tips, along with all the...
We introduce Flamingo, a single visual language model (VLM) that sets a new state of the art in few-shot learning on a wide range of open-ended multimodal tasks.
When I joined DeepMind as COO, I did so in large part because I could tell that the founders and team had the same focus on positive social impact. In fact, at DeepMind, we now champion a term that perfectly captures my own values and hopes for integrating technology into people’s daily lives: pione
DuckDB, Polars, and Pandas compared: Performance, memory, and scalability for large datasets. Benchmarks and practical insights.
An informal primer to causal analysis designs and data structures
If you are reading this, you are probably a Ravenclaw. Or a Hufflepuff. Certainly not a Slytherin … but maybe a Gryffindor? In this blog post, we let three subjective Bayesians predict the outcome of ten coin flips. We will derive prior predictions, evaluate their accuracy, and see how fortune favou
Using LLMs is often intertwined with search engine calls, so it makes sense to teach LLMs how to make these calls during training. Search engine API …
Here I illustrate how to fit GLMMs with the R package brms, and compare to Jags and lme4.
In response to my remark in this post, “So, what to do? I don’t know, exactly! There’s no Platonically correct prior for (mu, tau).
By Tobias Günther Branches are one of the core concepts in Git. And there's an endless amount of things you can do with them. You can create and delete them, rename and publish them, switch and compare them... and so much more. My intention with this...
We’re tickled pink to announce a v2 release of our collection of R related GitHub Actions at https://github.
This post is a complementary material for my talk at rstudio::conf 2022 (which is happening TODAY!!!)! I’m writing this really quick, from the hotel room, for anyone interested to see the code used to create the plot that it is on my talk: The plot uses data from the GitHub API, collected with the h
Welcome! This illustrated series tells a story about why GitHub is so powerful for supporting, reusing, contributing, and failing safely.
How can I download all issues information from Gitlab or Github and create a summary report of my commit messages for my client?
Posted by Sharan Narang and Aakanksha Chowdhery, Software Engineers, Google Research In recent years, large neural networks trained for language un...
We're celebrating TensorFlow's fifth birthday way five ways you can use and learn about our machine learning framework.
When It Comes to Forecasting Connections Within a Network
Taylor Rodgers, Senior Data Scientist and project lead at PKGlobal, walks through creating a powerful Shiny application with shinyMatrix and plotly for engineers, manufacturers, and plant workers.
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
Créée dans le cadre d’un partenariat de recherche entre Criteo et Inria, l’équipe-projet FAIRPLAY se donne pour mission d’étudier l’impact de l’IA sur la conception de places de marchés transparentes et équitables. Retour sur la genèse de cette équipe-projet commune Criteo – Inria – Institut Polytec
I am Julien Beaulieu, and I work as a data scientist. I write about Data Science, learning and productivity. Contact me to have a chat.
With the power and popularity of the scikit-learn for machine learning in Python, this library is a foundation to any practitioner's toolset. Preview its core methods with this review of predictive modelling, clustering, dimensionality reduction, feature importance, and data transformation.
Applying design guidelines to slides with {xaringanthemer} At a recent R-Ladies Seattle meetup, Silvia Canelón gave a great presentation on getting {xaringan} slides set up and deployed with GitHub pages for easy sharing.
I am Satya Mallick. I blog about Computer Vision and Machine Learning, and publish code and tutorials in OpenCV ( C++ & Python ).
From Gan To Wgan Aug 20, 2017 by Lilian Weng ← How To Explain The Prediction Of A Machine Learning Model Anatomize Deep Learning With Information Theory →.
Sample answers to 21 machine learning interview questions that could appear in any data scientist or machine learning engineer interview.
You must understand your data in order to get the best results from machine learning algorithms. The fastest way to learn more about your data is to use data visualization. In this post you will discover exactly how you can visualize your machine learning data in Python using Pandas. Let's get start
Adrin Jalali and Cailean Osborne of Probabl deep dive into how open source projects are managing the surge of AI-generated contributions, highlighting pragmatic principles and policies to protect maintainer bandwidth.
Creating AI that respects all identities equally starts with having more inclusive datasets. Today, we are sharing our work with researchers to help...
A note that I wrote for a computer science class I taught all the way back in 2010
Are you Data Scientists or Software Developers?! I think the best Data Scientists are both. This little exchange was a spicy first question I got after walking another state agency through some of our internal travel time estimation tooling back at Queensland Fire and Emergency Services. And I’ve on
Sélection des données de collecte, apport des experts métiers, méthodes de correction…. Tour d'horizon des méthodes permettant de réduire les dérives d'un modèle de machine learning ou de deep learning.
Vous connaissez le concept de déni plausible appliqué aux mots de passe ? L'idée c'est que si quelqu'un chope votre coffre-fort de passwords et tente de le ...
[1] \"Created: Wed Apr 1 16:43:54 2015\" See the introduction for an overview.
Machine learning is great… until you have to explain it. Stakeholders are normally non-technical, C-suites that ultimately want to know what the model does for the business. And how it helps increase revenue or decrease costs. A new R package, modelDow...
R has countless packages. This is a collection of the ones I found to be the most useful for data scientists and software developers alike.
The NumFOCUS blog covers topics of interest to data scientists and programmers. Interviews with open source maintainers, open science updates, and more.
class: center, middle, inverse, title-slide # Writing dynamic and reproducible documents ## An introduction to R Markdown ### Olivier Gimenez ### November 2020 --- # Credits - Garrett Grolemund [RStudio webinar](https://github.
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
Learning by doing: migrating to Quarto from Bookdown I just had rather a lot of fun working with Ileana Fenwick to convert a book to Quarto from RMarkdown! Given that Quarto is relatively new and there’s not yet an excess of resources beyond the official docs, we’ve documented how we did it.
Les outils CLI modernes (ripgrep, fd, bat, fzf, jq, yq) ne sont pas implémenté par défault dans les workflow d'agents IA, et en fait ils peuvent avoir un impact mesurable sur la consommation de tokens et la performance des agents
Learn the power of parameterized reporting with RMarkdown to effortlessly generate multiple reports, saving hours of manual work.
Shiny apps are easy to build, but often they are designed and implemented poorly. Learn how to make professional-grade Shiny apps.
Gamatogel merupakan link situs toto togel terpercaya sebagai bandar toto dan slot online terlengkap. Menyediakan pasaran lengkap, akses mudah, dan layanan profesional untuk pemain Indonesia.
If you think you mastered the language, you’ve got to read this
In this blog post of the “Quarto Q&A” series you will learn how to publish your Quarto project as a Docker container.
This blog post is an in-depth guide on how to start blogging with Quarto.
Inspired by the saying “An apple a day keeps the doctor away”, this project titled “A Quarto tip a day keeps the docs away” is a playful attempt to share Quarto tips for a month leading up to my rstudio::conf(2022) keynote on Quarto.
Using GitHub actions to render and publish a Quarto website.
We used to have a language war, then peaceful polyglot co-existence. Now, it’s clear that we’re actively better off learning from each other. A reflection on 2025, posit::conf, what R and python stacks can learn from each other, and the criticality of diversity in open source
Anyone who has created their own R package has probably come across Hilary Parker’s awesome blogpost, that walks you through creating your very first R package. The comprehensive detail on everything R packages can be found in Hadley Wickham’s superb book. In this post I am going to walk through som
I often get asked how to fit different multilevel models (or individual growth models, hierarchical linear models or linear mixed-models, etc.) in R. In this…
A collection of some R and data-analysis workflow write-ups that have piqued my interest over the past year or so.
When you've got multiple plots in a report made with R, aligning the axes can be challenging. Here's how we do it.
If you haven’t heard of Docker, it is a system that allows projects to be split into discrete units (i.e. containers) that each operate within their own virtual environment. Each container has a blueprint written in its Dockerfile that describes all of the operating parameters including operating sy
<div style = \"width:60%; display: inline-block; float:left; \"> One of my goals for 2016 is to improve my ability to understand different statistical/machine learning problems. I have an educational background in economics, so I have spent a good deal of time studying and using linear modeling in it’
<div style = \"width:60%; display: inline-block; float:left; \"> Imagine you could: Take a picture with your phone of a bird in your backyard. Upload the foto to an app. The app tells you what kind of bird it is. In this tutorial, you will learn how to quickly build an app that does just that – using
Structuring R projects is a necessary evil: nobody likes doing it, but everybody enjoys a well-structured, efficient project. This post takes you through some of the key principles of structuring a project well. The post Structuring R projects appeared first on Doodling in Data.
<div style = \"width:60%; display: inline-block; float:left; \"> Introduction Making Multiple Plots on the Same Subject Preparing the Data Writing Functions to Generate Multiple Plots Making Custom Plot Themes Updating Plot Themes Introduction There are often situations when you need to perform repeti
Website - Youtube - About - Talks - Books - Packages - RSS Reproducibility with Docker and Github Actions for the average R enjoyer R proramming Published November 19, 2022 Permanently moved.
Translation capabilities in Shiny apps can help data scientists communicate with an international audience. Nicola Rennie from Jumping Rivers shares her experience developing multilingual Shiny apps.
In this series, we walk through lesser-known tips and tricks to help you work more effectively and efficiently in R Markdown. This first post focuses on working with R Markdown in the RStudio IDE.
In this series, we show you lesser-known tips and tricks to help you work more effectively and efficiently in R Markdown. This second post focuses on cleaning up your R Markdown code.
In this series, we walk through lesser-known tips and tricks to help you work more effectively and efficiently in R Markdown. This third post focuses on features that save you time and trouble.
There are so many RStudio shortcuts out there but these are my TOP5 that I regularly use 😊 I love them because they usually make your life easier.
We are thrilled to announce the release of vetiver, a framework for MLOps tasks in R and Python. Use vetiver to version, share, deploy, and monitor a trained model.
FINALLY Deployed a Model to production, it only took 11 Months!!!!! I've been programming in python for about 2 years now, and I wanted to learn how to deploy a machine learning model in a production system.
Regular expressions. How they can be cruel! Well we’re here to make them a tad easier. To do so we’re going to make use of the {stringr} package install.packages(\"stringr\") library(\"stringr\") We’re going to use the str_detect() and str_subset() functions. In particular the latter. These have the syn
It isn't my job to disappoint people, but I'm good at it.
Anders Huitfeldt writes: Thank you so much for discussing my preprint on effect measures (“Count the living or the dead?”) on your blog! I really appreciate getting as many eyes as possible on this work; having it highlighted on by you is the kind of thing that can really make the snowball start rol
Got a Quarto website, but no blog? We can fix that!
Weights & Biases, developer tools for machine learning
We’re working on the next dplyr release.
In this post, we explore possible challenges to putting Shiny in production and how to overcome them.
Last week, we were very excited to host our first Shiny in Production conference! Attendees gathered in The Catalyst in Newcastle for two days of workshops and talks focusing on all things related to Shiny, building dashboards, and cool things you can do in R. On day one, we ran three workshops: Jac
The organisation for Shiny in Production is well under way - our list of speakers is now up on the conference website, and registration is open, with Early Bird tickets available until July 31st! Read on for more details.
Researcher, educator, and journalist with data science expertise.
Many, including prominent scientists, seem to misunderstand the true cost of biomedical research and the fact that universities subsidize it beyond what they receive from the NIH.
Lorsque vous essayez de tester des modèles, il est complexe de trouver des jeux de données intéressants. Dans cet article, nous faisons un petit tour de quelques sites vous permettant de vous lancer…
In hypothesis tests, use significance levels and p-values to determines statistical significance. Learn how these tools work.
Locking down R package dependencies and versions is a solved problem, thanks to the easy-to-use renv package. System dependencies — those Linux packages that
In my work, writing tests serves three purposes: making sure things work, documenting my understanding, preventing future errors. When I was starting out with testing, I had a hard time understanding what I should be writing tests for. As a beginner, I just assumed my code worked–I was staring right
Claude Code, c'est super puissant... mais faut avouer que dans un terminal, quand l'IA commence à enchaîner les appels d'outils dans tous les sens, on se ...
Dans ces quelques lignes je vais vous expliquer comment concevoir votre propre package R. Ne partez pas ! Il n’y a pas d’appréhension à avoir, c’est
Retour sur l'intervention de Vincent aux 6e Rencontres R d'Anglet : \"Encapsuler une application R avec Docker\".
La version 0.3.3 de golem est disponible sur le CRAN, elle propose une nouvelle approche de construction d'images docker pour le déploiement de vos
The R task Force - R experts for all your needs
The R task Force - R experts for all your needs
The R task Force - R experts for all your needs
Tidy notes I took from Dave Robinson’s screencasts #TidyTuesday
An R code walkthrough for treatment timelines or ‘swimmer’ plots. These can help visualize treatment or measurement patterns, time-varying covariates, outcomes, and loss to follow-up in longitudinal data settings.
One of the most useful features of any version control system is the ability to \"undo\" your mistakes. In Git, \"undo\" can mean many slightly different things.
Visual Studio Code is one of the most popular code editors used by software developers. While it has many great features built-in, there are a lot of extensions you can install to increase your productivity. We just published a video on the freeCode...
Learn Azure ML and machine learning with Bea Stollnitz.
We don't talk about Quarto Until now! By Alison Hill in rmarkdown April 4, 2022 Thumbnail image from the Official Disney Fan Club website Background Early last year, I was busily checking Quarto, and totally terrified of checking Twitter.
Announcing the Closeread Prize winners! Prepare to be amazed by these stunning scrollytelling experiences created in Quarto.
This article will be updated to reflect the latest languageserver features.
Last year I wrote an R package with a weird name “xaringan”. Although I have documented it, I have never explained why I preferred the underlying HTML5 presentation framework remark.js …
Bot twitter Bot twitter sur l'ouverture du pont Chaban Delmas à Bordeaux Site web perso Code source du site Application isochrones Calcul d'isochrones et observations des équipements publics à proximité Nettoyage résultats électoraux Passage des données data.
Shiny enables you to write powerful interactive web applications entirely in R. Using R you create a user interface and server and Shiny compiles your code into the HTML, CSS and JavaScript needed …
Happy birthday easystats! A retrospective Jan 27, 2022 Happy birthday easystats! Two years ago, which feels like yesterday, we celebrated the easystats project’s first anniversary.
For everything from styling text and customizing color palettes to creating your own geoms, these ggplot2 add-ons deserve a place in your R data visualization toolkit. Plus, a bonus list of packages to explore on your own.
What’s complicated about size and resolution ? Have you ever tried to reproduce a plot like the first one and make minor changes on the size or resolution and end up with something like the second plot ?
Easily work and ggplot SpatRasters - tidyterra provides tidyverse methods for terra objects and geom functions for plotting with ggplot2....
The authoritative, most-used AI textbook, adopted by over 1500 schools.
Welcome :) 1 Your last-ever bookmark Thanks for stopping by.
Help software engineers interview at their best. The best-selling book in computer science for 4 years running. Written by a former member of Google's hiring committee, and the consultant on engineering hiring for many of the top tech companies.
This is a guide on how to conduct data analysis in the field of data science, statistics, or machine learning.
This book introduces concepts and skills that can help you tackle real-world data analysis challenges. It covers concepts from probability, statistical inference, linear regression and machine learning and helps you develop skills such as R programming, data wrangling with dplyr, data visualization
This book introduces concepts and skills that can help you tackle real-world data analysis challenges. It covers concepts from probability, statistical inference, linear regression and machine learning and helps you develop skills such as R programming, data wrangling with dplyr, data visualization
DSxD’s Future of Data Science Book One part of the Data Science by Design (DSxD) initiative that we are especially excited about is showcasing the work created by the newly established DSxD community.
Bookdown for ‘Data Science in Education Using R’ by Ryan A. Estrellado, Emily A. Freer, Joshua M. Rosenberg, and Isabella C. Velásquez to be published by Routledge in 2024
The Deep Learning textbook is a resource intended to help students and practitioners enter the field of machine learning in general and deep learning in particular.
DescriptionDeep learning is a group of exciting new technologies for neural networks. Through advanced training techniques and neural network architectural components, it is now possible to create neu
Machine learning systems are both complex and unique. Complex because they consist of many different components and involve many different stakeholders. Unique because they're data... - Selection from Designing Machine Learning Systems [Book]
This is a guide on how to conduct Meta-Analyses in R.
Beginners with little background in statistics and econometrics often have a hard time understanding the benefits of having programming skills for learning and applying Econometrics. ‘Introduction to Econometrics with R’ is an interactive companion to the well-received textbook ‘Introduction to Econ
A book about engineering shiny application that will later be sent to production. This book cover project management, structuring your project, building a solid testing suite, and optimizing your codebase. We describe in this book a specific workflow: design, prototype, build, strengthen and deploy.
The Epidemiologist R Handbook Welcome R for applied epidemiology and public health Usage: This handbook has been used over 3 million times by 850,000 people around the world.
Thank you for your interest in the Statistics for Ecologists book.
Flexible Imputation of Missing Data, Second Edition
Chapter 1 Getting started Forecasting has fascinated people for thousands of years, sometimes being considered a sign of divine inspiration, and sometimes being seen as a criminal activity.
A guide to making visualizations that accurately reflect the data, tell a story, and look professional.
Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can... - Selection from Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow, 2nd Edition [Book]
This book introduces the integrated nested Laplace approximation (INLA) for Bayesian inference and its associated R package R-INLA.
ISLR tidymodels labs 1 Introduction This book aims to be a complement to the 2nd edition An Introduction to Statistical Learning book with translations of the labs into using the tidymodels set of packages.
Book on using JavaScript with R for visualisations, web development, and computations.
This is a short overview of why averages don’t work well for evaluating Likert scale or other ordinal-scale data, and what to do instead, with examples using R.
Highly recommended by JASA, Technometrics, and other leading statistical journals, the first two editions of this bestseller showed how to easily perform complex linear mixed model (LMM) analyses via a variety of software programs. Linear Mixed Models: A Practical Guide Using Statistical Software, T
The past decade has witnessed the broad adoption of artificial intelligence and machine learning (AI/ML) technologies. However, a lack of oversight in their widespread... - Selection from Machine Learning for High-Risk Applications [Book]
An open-source and fully-reproducible electronic textbook for teaching statistical inference using tidyverse data science tools.
This leading textbook provides a comprehensive introduction to the fields of pattern recognition and machine learning. It is aimed at advanced undergraduates or first-year PhD students, as well as researchers and practitioners. No previous knowledge of pattern recognition or machine learning concept
“Probabilistic Machine Learning” - a book series by Kevin Murphy
Probabilistic Machine Learning: Advanced Topics by Kevin Patrick Murphy.
For many researchers, Python is a first-class tool mainly because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual... - Selection from Python Data Science Handbook [Book]
Python Data Science Handbook Jake VanderPlas This website contains the full text of the Python Data Science Handbook by Jake VanderPlas; the content is available on GitHub in the form of Jupyter notebooks.
The \"Python Machine Learning (3rd edition)\" book code repository - rasbt/python-machine-learning-book-3rd-edition
An open source book describing modern and efficient workflows for developing and maintaining Python packages!
Python for Data Analysis is concerned with the nuts and bolts of manipulating, processing, cleaning, and crunching data in Python. It is also a practical, modern introduction to... - Selection from Python for Data Analysis [Book]
Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems [Géron, Aurélien] on Amazon.com. *FREE* shipping on qualifying offers. Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelli
This book showcases short, practical examples of lesser-known tips and tricks to helps users get the most out of these tools. After reading this book, you will understand how R Markdown documents are transformed from plain text and how you may customize nearly every step of this processing. For exam
Learn how to create a package, the fundamental unit of shareable, reusable, and reproducible R code.
Learn how to create a package, the fundamental unit of shareable, reusable, and reproducible R code.
This book will teach you how to do data science with R: You’ll learn how to get your data into R, get it into the most useful structure, transform it, visualise it and model it. In this book, you will find a practicum of skills for data science. Just as a chemist learns how to clean test tubes and s
An R reproducibility toolkit for the practical researcher.
This document is full of supplemental resources and content from the Shiny in Production Workshop delievered at rstudio::conf 2019.
A book for Spatial Statistics for Data Science with R.
This open educational resource contains information to improve statistical inferences, design better experiments, and report scientific research more transparently.
This open educational resource contains information to improve statistical inferences, design better experiments, and report scientific research more transparently.
The tidymodels framework is a collection of R packages for modeling and machine learning using tidyverse principles. This book provides a thorough introduction to how to use tidymodels, and an outline of good methodology and statistical practice for phases of the modeling process.
| | | High-Dimensional Data Analysis with Low-Dimensional Models: Principles, Computation, and Applications | Basic Information The book covers new mathematical (statistical, geometrical, computational) principles for high-dimensional data analysis, with scalable optimization methods and their appli
Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems [Géron, Aurélien] on Amazon.com. *FREE* shipping on qualifying offers. Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelli
ggplot2: Elegant Graphics for Data Analysis (3e) Welcome This is the on-line version of work-in-progress 3rd edition of “ggplot2: elegant graphics for data analysis” published by Springer.
Miguel Hernan Kolokotrones Professor of Biostatistics and Epidemiology Epidemiology, Harvard T.
10 Causality Machine learning exploits all available information to make predictions – and there are many ways to predict things.
Veridical Data Science The Practice of Responsible Data Analysis and Decision Making This is the Open Access web version of Veridical Data Science.
I’m making freely available the first version of something I’ve wanted to do for a long time. I’m an advanced R user, but I’m very limited in both, Python and Julia. However…
A community resource covering Social Science — Awesome Computational Social Science.
A community resource covering Data Science and Leadership — Awesome Data Leadership.
A community resource for R covering Games and Fun — Awesome R Games.
A community resource for R covering Shiny and Web Development — Awesome R Shiny.
A community resource for Python covering Deep Learning and TensorFlow — Awesome TensorFlow.
A community resource for Python covering Computer Vision and Transformers — Awesome Visual Transformer.
A community resource for Python covering Machine Learning — Best of ML Python.
A community resource covering Docker and DevOps — Docker Labs.
A community resource for R covering Community — French R Users.
Hacker News new | past | comments | ask | show | jobs | submit login 1.
A community resource for R covering Public Statistics — InseeFr GitHub.
A community resource for Python covering Data Science — Jupyter Notebooks Gallery.
A computing-focused community centered around link aggregation and discussion.
A community resource for Python covering Machine Learning — ML Cheatsheets.
A community resource covering Machine Learning and Community — ML Collective.
A community resource for R covering Causal Inference — R-Causal.
A community resource for R covering Education and Video — RStudio Webinars.
A community resource for R covering Community — State of the R.
A community resource for R covering Machine Learning and Statistics — Statistical Learning with R.
A community resource covering Algorithms and Programming — The Algorithms.
Top Python Libraries of 2025 (11th Edition) We tried really hard not to make this an AI-only list.
A community resource for Python covering Deep Learning and Transformers — Transformers Tutorials.
Introduction to Causal Inference. A free online course on causal inference from a machine learning perspective.
Develop your Python 3 skills in our comprehensive course. Start coding and build versatile applications.
Offered by DeepLearning.AI. In this course, you will: - Learn about GANs and their applications - Understand the intuition behind the ... Enroll for free.
Course info | When | Tue & Thu 10:05 - 11:20am | | Where | Perkins LINK 070 (Seminar 4) | Teaching team | Instructor | Mine Çetinkaya-Rundel | OH: Mon 1 - 3pm & Wed by appointment at Old Chem 213 | | | TA | Kyle Burris | OH: Wed 9 - 10am & Fri 10 - 11am at Old Chem 211A | Texts All texts are freely
| Date | Topic | Reading | Notes | | |---|---|---|---|---| | Mon, Aug 28 | Introduction [Slides] | Codeschool - Try R | || | Wed, Aug 30 | Using git and github [Slides] | Happy Git and GitHub for the useR, Try github, Trump Tweet blog post | RStudio Server - Saxon or OIT VM Screencast - git & github
A free course designed for people with some coding experience, who want to learn how to apply deep learning and machine learning to practical problems.
Materials for Gov 2003: Causal Inference with Applications
In this segment, we understand what an image is when represented on a computer, and how you can use the Images.
MIT's introductory course on deep learning methods and applications.
Course Description This course provides a broad introduction to machine learning and statistical pattern recognition.
CS25 has become one of Stanford's hottest and most seminar courses, featuring top researchers at the forefront of Transformers research such as Geoffrey Hinton, Ashish Vaswani, and Andrej Karpathy. Our class has an incredibly popular reception within and outside Stanford, and millions of total views
<p>Welcome to Deployment of Machine Learning Models, the<strong> most comprehensive machine learning deployments online course available to date. </strong>This course will show you how to take your machine learning models from the research environment to a fully integrated production environment<str
<p>Ever wondered how AI technologies like <strong>OpenAI</strong> <strong>ChatGPT</strong>,<strong> GPT-4</strong>, <strong>DALL-E</strong>, <strong>Midjourney</strong>, and <strong>Stable Diffusion</strong> really work? In this course, you will learn the foundations of these groundbreaking applicat
<p><strong>Welcome to Production-Grade ML Model Deployment with FastAPI, AWS, Docker, and NGINX!</strong></p><p>Unlock the power of seamless ML model deployment with our comprehensive course, <em>Production-Grade ML Model Deployment with FastAPI, AWS, Docker, and NGINX.</em> This course is designed
::session_info(\"installed\") sessioninfo## ─ Session info ─────────────────────────────────────────────────────────────── ## setting value ## version R version 4.
[R] Adding Nested Random Effects to MCMCglmm Marian L.
It sounds like the output value simply isn't being received by the browser. One thing you might want to try is to put this at the top of your app, and then check what shows up in your logs: options(shiny.trace = TRUE) It will record all the messages sent between the R process and the browser. If you
I've tried modifying a shiny app from the demo, and also copied directly the Hello Shiny app into two files. I can get the UI from Hello, but no graph. From my modification of another CLT app (tgou...
The guide Table of contents This guide is under development, and the authors welcome feedback and contributions.
Want to get a better overview of the different modeling approaches? In less than 100 pages, Modeling Mindsets, The Many Cultures of Learning From Data elucidates the worldviews behind various statistical modeling and machine learning mindsets.
Master the command line, in one page. Contribute to jlevy/the-art-of-command-line development by creating an account on GitHub.
Cleaning data can take hundreds or thousands of lines.
Collection of preprints focusing on the practical side of data science workflows and statistical analysis. Curated by Jennifer Bryan and Hadley Wickham.
RzineArticles de méthodes pour les Sciences Humaines et Sociales ISSN 2743-8791 - Revue de documents computationnels
Dalam beberapa tahun terakhir, dunia permainan daring telah berkembang pesat, terutama di sektor permainan kartu seperti BandarQQ dan BandarQ.
Better machine learning by thinking like a statistician. About model interpretation, paying attention to data, and always staying critical. Click to read Mindful Modeler, by Christoph Molnar, a Substack publication with tens of thousands of subscribers.
Find ML News articles & tutorials from leading machine learning practitioners. Fully Connected: An ML community from Weights & Biases.
A GUI for Pandas DataFrames. Contribute to adamerose/PandasGUI development by creating an account on GitHub.
Data quality assessment and metadata reporting for data frames and database tables - rstudio/pointblank
Python GUIs for Humans! PySimpleGUI is the top-rated Python application development environment. Launched in 2018 and actively developed, maintained, and supported in 2024. Transforms tkinter, Qt, ...
A universal package of scraper scripts for humans. Contribute to DarshanDeshpande/Scrapera development by creating an account on GitHub.
The first machine learning framework that encourages learning ML concepts instead of memorizing class functions. - GitHub - anish-lakkapragada/SeaLion: The first machine learning framework that en...
Dependency Management with roxygen-style Comments. Contribute to analythium/deps development by creating an account on GitHub.
Prototype UI for Shiny Apps. Contribute to ashbaldry/designer development by creating an account on GitHub.
A general-purpose computational engine for data analysis, drake rebuilds intermediate data objects when their dependencies change, and it skips work when the results are already up to date. Not every execution starts from scratch, there is native support for parallel and distributed computing, and c
Provides a collection of commonly used univariate and multivariate time series forecasting models including automatically selected exponential smoothing (ETS) and autoregressive integrated moving average (ARIMA) models. These models work within the fable framework provided by the fabletools package,
Provides a series of aliases to commonly used but difficult to remember ggplot2 sequences.
Extension of 'ggplot2', 'ggstatsplot' creates graphics with details from statistical tests included in the plots themselves. It provides an easier syntax to generate information-rich plots for statistical analysis of continuous (violin plots, scatterplots, histograms, dot plots, dot-and-whisker plot
Ease the creation of time-to-event (i.e. survival) endpoint figures. The modular functions create figures ready for publication. Each of the functions that add to or modify the figure are written as proper ggplot2 geoms or stat methods, allowing the functions from this package to be combined with an
An opinionated framework for building a production-ready Shiny application. This package contains a series of tools for building a robust Shiny application from start to finish.
Creates presentation-ready tables summarizing data sets, regression models, and more. The code to create the tables is concise and highly customizable. Data frames can be summarized with any function, e.g. mean(), median(), even user-written functions. Regression models are summarized and include th
Hugging Face state-of-the-art models in R. Contribute to farach/huggingfaceR development by creating an account on GitHub.
leafdown: drilldown functionality for leaflet choropleths - hoga-it/leafdown
The time series forecasting framework for use with the tidymodels ecosystem. Models include ARIMA, Exponential Smoothing, and additional time series models from the forecast and prophet packages. Refer to \"Forecasting Principles & Practice, Second edition\" (<https://otexts.com/fpp2/>). Refer to \"Pro
When getting time series data ready for analysis, you might be confronted with the following two challenges: padr aims to make light work of preparing time series data by offering the two main functions thicken and pad.
This vignette describes the rvar() datatype, a multidimensional, sample-based representation of random variables designed to act as much like base R arrays as possible (e.
Dynamic R prompt. Contribute to gaborcsardi/prompt development by creating an account on GitHub.
A complete and consistent functional programming toolkit for R.
Interactive data tables for R, based on the React Table JavaScript library. Provides an HTML widget that can be used in R Markdown or Quarto documents, Shiny applications, or viewed from an R console.
The renv package helps you create reproducible environments for your R projects.
Contribute to rstudio/shinytest2 development by creating an account on GitHub.
timevis: Create Interactive Timeline Visualizations in R - CRAN: http://cran.
Collaborative writing and editing of R Markdown (or Quarto / Sweave) documents. The local .Rmd (or Quarto / .Rnw) is uploaded as a plain-text file to Google Drive. By taking advantage of the easily readable Markdown (or LaTeX) syntax and the well-known online interface offered by Google Docs, collab
The vitae package makes creating and maintaining a Résumé or CV with R Markdown simple.
Give your xaringan slides some style with xaringanthemer. Easy slide and plot themes for xaringan slides.
This document aims to be a self-contained, mathematically precise overview of transformer architectures and algorithms (*not* results). It covers what transformers are, how they are trained, what they are used for, their key architectural components, and a preview of the most prominent models. The r
Recent text-to-image generation methods provide a simple yet exciting conversion capability between text and image domains. While these methods have incrementally improved the generated image fidelity and text relevancy, several pivotal gaps remain unanswered, limiting applicability and quality. We
The dominant sequence transduction models are based on complex recurrent or convolutional neural networks in an encoder-decoder configuration. The best performing models also connect the encoder and decoder through an attention mechanism. We propose a new simple network architecture, the Transformer
Measuring algorithmic bias is crucial both to assess algorithmic fairness, and to guide the improvement of algorithms. Current methods to measure algorithmic bias in computer vision, which are based on observational datasets, are inadequate for this task because they conflate algorithmic bias with d
Performance of machine learning algorithms depends critically on identifying a good set of hyperparameters. While recent approaches use Bayesian optimization to adaptively select configurations, we focus on speeding up random search through adaptive resource allocation and early-stopping. We formula
We propose a new framework for estimating generative models via an adversarial process, in which we simultaneously train two models: a generative model G that captures the data distribution, and a discriminative model D that estimates the probability that a sample came from the training data rather
While deep learning has enabled tremendous progress on text and image datasets, its superiority on tabular data is not clear. We contribute extensive benchmarks of standard and novel deep learning methods as well as tree-based models such as XGBoost and Random Forests, across a large number of datas
Currently, it is hard to reap the benefits of deep learning for Bayesian methods, which allow the explicit specification of prior knowledge and accurately capture model uncertainty. We present...
Background The analysis of microbial communities through DNA sequencing brings many challenges: the integration of different types of data with methods from ecology, genetics, phylogenetics, multivariate statistics, visualization and testing. With the increased breadth of experimental designs now be
Addressing the heterogeneity of both the outcome of a disease and the treatment response to an intervention is a mandatory pathway for regulatory approval of medicines. In randomized clinical trials (RCTs), confirmatory subgroup analyses focus on ...
While the Transformer architecture has become the de-facto standard for natural language processing tasks, its applications to computer vision remain limited. In vision, attention is either applied in conjunction with convolutional networks, or used to replace certain components of convolutional net
Evaluating generative adversarial networks (GANs) is inherently challenging. In this paper, we revisit several representative sample-based evaluation metrics for GANs, and address the problem of how to evaluate the evaluation metrics. We start with a few necessary conditions for metrics to produce m
Language models (LMs) are becoming the foundation for almost all major language technologies, but their capabilities, limitations, and risks are not well understood. We present Holistic Evaluation of Language Models (HELM) to improve the transparency of language models. First, we taxonomize the vast
Randomized Controlled Trials (RCTs) may suffer from limited scope. In particular, samples may be unrepresentative: some RCTs over- or under- sample individuals with certain characteristics compared to the target population, for which one wants conclusions on treatment effectiveness. Re-weighting tri
In the past few years we have seen the meteoric appearance of dozens of foundation models of the Transformer family, all of which have memorable and sometimes funny, but not self-explanatory, names. The goal of this paper is to offer a somewhat comprehensive but simple catalog and classification of
Interpretability in machine learning (ML) is crucial for high stakes decisions and troubleshooting. In this work, we provide fundamental principles for interpretable ML, and dispel common misunderstandings that dilute the importance of this crucial topic. We also identify 10 technical challenge area
As machine learning systems become ubiquitous, there has been a surge of interest in interpretable machine learning: systems that provide explanation for their outputs. These explanations are often used to qualitatively assess other criteria such as safety or non-discrimination. However, despite the
Machine-learning models have demonstrated great success in learning complex patterns that enable them to make predictions about unobserved data. In addition to using models for prediction, the ability to interpret what a model has learned is receiving an increasing amount of attention. However, this
Inspired by the Kolmogorov-Arnold representation theorem, we propose Kolmogorov-Arnold Networks (KANs) as promising alternatives to Multi-Layer Perceptrons (MLPs). While MLPs have fixed activation functions on nodes (\"neurons\"), KANs have learnable activation functions on edges (\"weights\"). KANs hav
CHAI’s mission is to develop the conceptual and technical wherewithal to reorient the general thrust of AI research towards provably beneficial systems.
An example `CLAUDE.md` prompt for R package development - CLAUDE.md
Claude R Tidyverse Expert. GitHub Gist: instantly share code, notes, and snippets.
Validate and Run GitHub Actions locally. Contribute to bahdotsh/wrkflw development by creating an account on GitHub.
A Positron IDE extension to create a rich in-line DuckDB SQL editor experience within R files. - belian-earth/duckdb-r-editor
Community-contributed instructions, prompts, and configurations to help you make the most of GitHub Copilot. - GitHub - github/awesome-copilot at cfb896c2325b8c0527a88362846d25b8080c5071
A curated list of awesome skills, hooks, slash-commands, agent orchestrators, applications, and plugins for Claude Code by Anthropic - hesreallyhim/awesome-claude-code
Contribute to jeremy-allen/claude-skills development by creating an account on GitHub.
posit team dedicated toolkit. Contribute to posit-dev/ptd development by creating an account on GitHub.
A collection of Claude Skills from Posit. Contribute to posit-dev/skills development by creating an account on GitHub.
An R package to interface with DuckLake lakehouses - tgerke/ducklake-r
Fast, small, and fully autonomous AI assistant infrastructure — deploy anywhere, swap anything 🦀 - zeroclaw-labs/zeroclaw
Slides for my presentation. Contribute to jfpuget/KaggleDays_Paris_2022 development by creating an account on GitHub.
some tools based on two conversions using claude. Contribute to topepo/bookdown-to-quarto development by creating an account on GitHub.
Code Wiki provides automatically generated, up-to-date documentation for your code. Stop wasting time on manual docs and explore codebase insights, API references, and architecture overviews instantly.
Learn how to install Copilot CLI so that you can use Copilot directly from the command line.
:ferris_wheel: A playground of enhancements and extensions for xaringan slides. - gadenbuie/xaringanExtra
Materials for rstudio::conf. Contribute to rstudio/rstudio-conf development by creating an account on GitHub.
Contribute to jbkunst/klassets development by creating an account on GitHub.
A curated list of awesome posts, videos, and articles on leading a data team (small and large) - ronikobrosly/awesome-data-leadership
Code of the NVIDIA winning solution to the 2nd OGB-LSC at the NeurIPS 2022 challenge with dataset PCQM4Mv2 - jfpuget/NVIDIA-PCQM4Mv2
Code and content for andrewheiss.com. Contribute to andrewheiss/ath-quarto development by creating an account on GitHub.
The hub for EleutherAI's work on interpretability and learning dynamics - EleutherAI/pythia
GPT RStudio addins that enable GPT assisted coding, writing & analysis - MichelNivard/gptstudio
gpttools extends gptstudio for package development to help you document code, write tests, or even explain code - JamesHWade/gpttools
⚡️⚡️⚡️ Self-hosted collaborative bookmark manager to collect, read, annotate, and fully preserve what matters, all in one place. - linkwarden/linkwarden
More efficient tidyverse code, using polars in the background - etiennebacher/tidypolars
An Open-source Toolkit for LLM Development. Contribute to Alpha-VLLM/LLaMA2-Accessory development by creating an account on GitHub.
A curated list of awesome work on causal inference, particularly in machine learning. - matthewvowels1/Awesome-Causal-Inference
A list of cool features of Git and GitHub. Contribute to tiimgreen/github-cheat-sheet development by creating an account on GitHub.
The definitive list of lists (of lists) curated on GitHub and elsewhere - jnv/lists
A curated list of awesome tools, resources and workflow tips making an awesome development environment. - jondot/awesome-devenv
🐶 (Re)constructing R computational environments. Contribute to gesistsa/rang development by creating an account on GitHub.
Awesome-LLM: a curated list of Large Language Model - Hannibal046/Awesome-LLM
moodymudskipper has 113 repositories available. Follow their code on GitHub.
Lab de @InseeFr. InseeFrLab has 283 repositories available. Follow their code on GitHub.
Demonstration of using a JavaScript ServiceWorker to communicate with a running Shiny/httpuv session in webR. - georgestagg/shiny-standalone-webr-demo
Home of StarCoder: fine-tuning & inference! Contribute to bigcode-project/starcoder development by creating an account on GitHub.
Contribute to mshumer/gpt-prompt-engineer development by creating an account on GitHub.
🐢 Open-Source Evaluation & Testing library for LLM Agents - Giskard-AI/giskard-oss
Gorilla: Training and Evaluating LLMs for Function Calls (Tool Calls) - ShishirPatil/gorilla
Contribute to tangandhara/stravaDashboard development by creating an account on GitHub.
Contribute to labsyspharm/smallmoleculesuite development by creating an account on GitHub.
Get up and running with Kimi-K2.5, GLM-5, MiniMax, DeepSeek, gpt-oss, Qwen, Gemma and other models. - ollama/ollama
There can be more than Notion and Miro. AFFiNE(pronounced [ə‘fain]) is a next-gen knowledge base that brings planning, sorting and creating all together. Privacy first, open-source, customizable an...
PyGWalker: Turn your dataframe into an interactive UI for visual analysis - Kanaries/pygwalker
Development environment for Quarto PDF reports. Contribute to ketchbrookanalytics/quarto-pdf-dev development by creating an account on GitHub.
Python interactive dashboards for learning data science - GeostatsGuy/DataScienceInteractivePython
Python interactive dashboards for learning data science - GeostatsGuy/DataScienceInteractivePython
A lightweight version of R Markdown (without using Pandoc or knitr) - yihui/litedown
Turns Data and AI algorithms into production-ready web applications in no time. - Avaiga/taipy
🙌 OpenHands: AI-Driven Development. Contribute to OpenHands/OpenHands development by creating an account on GitHub.
Flexible filter for Shiny. Contribute to the-y-company/flexfilter development by creating an account on GitHub.
End-to-End Workflow with Posit Team presentation, August 2024: Using pins for Shiny with ever-changing data - posit-marketing/shiny-calendar
Interactive timeline visualization of hierarchical items. - padamson/stratvis
How to open an R Shiny modal popup from a hyperlink in a datatable - epi-interactive/Datatable_Overlay
Github README profile. Contribute to ddotta/ddotta development by creating an account on GitHub.
Prompt, run, edit, and deploy full-stack web applications using any LLM you want! - stackblitz-labs/bolt.diy
A modular R ecosystem for building modern web applications, the web way. - hyperverse-r
Developing data analyses pipelines around open source, open data, and open communities has shown great successes. The most used machine-learning tools t…
In this prompt guide for GitHub Copilot, two GitHub developer advocates, Rizel and Michelle, will share examples and best practices for communicating your desired results to the AI pair programmer.
Quarto Extension to enable DesignMode. Contribute to EmilHvitfeldt/quarto-designmode development by creating an account on GitHub.
:straight_ruler: Analytics and telemetry for Shiny applications. - GitHub - devOpifex/shinymetrics: :straight_ruler: Analytics and telemetry for Shiny applications.
Tinker with a real neural network right here in your browser.
Recently, I had the opportunity to showcase tidymodels in workshops and talks. Because of my vantage point as a user, I figured it would be valuable to share what I have learned so far. Let’s begin by framing where tidymodels fits in our analysis projects. The diagram above is based on the R for Dat
Lecture 1 gives a broad introduction to computer vision and machine learning. We give a brief history of the two fields, starting in the 1950s and leading up...
Enregistrement du Meetup R Lille et Tunis R User Group du 24 février 2022 : http://meetup.rlille.fr/events/283419297Plus de Meetups sur http://meetup.rlille...
ECCV 2020 Workshop on Sensing, Understanding and Synthesizing HumansWebsite: https://sense-human.github.io/
Lecture 1 gives a broad introduction to computer vision and machine learning. We give a brief history of the two fields, starting in the 1950s and leading up...
Based on joint work with Yi Zhang, Arturs Backurs, Ronen Eldan, Suriya Gunasekar, Tal Wagner https://arxiv.org/abs/2206.04301.
This git tutorial for beginners is designed to teach you the git command line tool and how it works with github. This beginner git tutorial teaches github fu...
This webinar breaks down one of the most esoteric concepts in the Tidyverse: list columns.
Partagez vos vidéos avec vos amis, vos proches et le monde entier
Profitez des vidéos et de la musique que vous aimez, mettez en ligne des contenus originaux, et partagez-les avec vos amis, vos proches et le monde entier.
This Python 3 tutorial course aims to teach everyone the basics of programming computers using Python. The course has no pre-requisites and avoids all but th...
We'll discuss R’s history of interoperability and the philosophy of Reticulate, the Reticulate-powered features in RStudio 1.2, and talk through a case study of a reticulated Shiny app
Présentation Presse Droits d'auteur Nous contacter Créateurs Publicité Développeurs Résilier vos abonnements Conditions d'utilisation Confidentialité Règles et sécurité Premiers pas sur YouTube Tester de nouvelles fonctionnalités © 2026 Google LLC.
Cette vidéo vous présente comment construire une application shiny à l'aide du package golem !Nous décrivons les différents fichiers de votre package (car ou...
A quick demonstration of our latest project, the dashboard-builder. Create R-shiny dashboards without writing any R-code. Learn more during our session at rs...
The Stanford School of Engineering has been at the forefront of innovation for nearly a century, creating pivotal technologies that have transformed the worlds of information technology, communications, medicine, energy, business and beyond. The faculty, students and alumni of Stanford Engineering h
Partagez vos vidéos avec vos amis, vos proches et le monde entier
More materials including practicals and exercises here: https://github.com/cwkx/materials
12 fév 2016 14:30 à 15:30 Cours Pourquoi l'apprentissage profond ? Yann LeCun L'apprentissage profond 12 fév 2016 14:30 à 15:30 Partager Facebook LinkedIn Bluesky Threads Copier le lien Flux RSS Audiovisuel Vendredi 12 février 2016 Amphithéâtre Maurice Halbwachs, Site Marcelin Berthelot En libre acc
In this webinar originally broadcast on June 6, 2019 in partnership with RStudio Community, Colin Fay from ThinkR shares many excellent insights and practica...
A comparison of formula and tidyverse syntaxes Amelia McNamara @AmeliaMN This talk is based on a paper I wrote, which is available as a pre-print via arXiv, https://arxiv.
The machine learning consultancy: https://truetheta.ioJoin my email list to get educational and useful articles: https://mailchi.mp/truetheta/true-theta-emai...
Tips and tricks learnt from building production {shiny} apps Monday 7th NovemberDelivered by Colin Fay, Data Scientist & R Hacker at ThinkRAbout the webinar:...
Learn how to use crew and callr to turn your synchronous Shiny app into an asynchronous one! 🚀 Follow-up video of my talk at the Shiny Gaterhings by @appsil...
03 - Theming Quarto Slides Exercise 1 In the workshop repo, there is a file called 03-exercise.
AGENTS.md is a simple, open format for guiding coding agents. Think of it as a README for agents.
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
Conference presentation about the 'distributions3' package for S3 probability distributions (and 'topmodels' for graphical model assessment) at useR! 2022: Slides, video, replication code, and vignette.
🤹 Shiny tips & tricks for improving your apps and solving common problems - daattali/advanced-shiny
This is the site for sharing our Data Visualization Labs for CS631 at Oregon Health & Science University.
Welcome! This data science & statistics artwork is available for free, open use by CC-BY (Creative Commons Attribution 4.
Andrew Gelman is a professor of statistics and political science at Columbia University.
My favorite R packages. Contribute to abichat/favoriteRpackages development by creating an account on GitHub.
Thèse de mathématiques appliquées par Antoine Bichat. Statistique – Apprentissage – Métagénomique – Arbre phylogénétique – Tests multiples – Processus stochastiques
I am a Research Scientist working in DeepMind's vision group.
I am a Senior Research Scientist at Google DeepMind in London, working on the multi-modal capabilities of Gemini.
As datasets become larger and more complex, the boundaries between data engineering and data science are becoming blurred.
JUDEA PEARL AND DANA MACKENZIE THE BOOK OF WHY: THE NEW SCIENCE OF CAUSE AND EFFECT New York: Basic Books, Published May 15, 2018 HOME PUBLICATIONS BIO CAUSALITY PRIMER WHY COEXISTENCE DANIEL PEARL FOUNDATION HOME PUBLICATIONS BIO CAUSALITY PRIMER WHY COEXISTENCE DANIEL PEARL FOUNDATION Preface Tabl
Making awesome automations with GitHub Actions rstudio::conf(2022) Talks GitHub Actions GitHub English Event: rstudio::conf(2022) Complementary materials Blog post: How important is GitHub Actions to RStudio/Posit? Code for a plot in my talk! Blog post: Monitoring quarto-dev repositories: Creating a
Bioicons contains free science illustrations for biologists, chemists, machine learning under permissive CC0, CC BY or MIT License.
Contribute to bamos/presentations development by creating an account on GitHub.
Welcome to my professional website. You will find a brief description of my research, teaching material, and information about my consulting activity at NRU.
The Models, Inference & Algorithms (MIA) Initiative at the Broad Institute supports learning and collaboration across the interface of biology and medicine with mathematics, statistics, machine learning, and computer science. Our weekly meetings are open and pedagogical, emphasising lucid exposition
Abstraction is at the heart of sketching due to the simple and minimal nature of line drawings.
CRAN Task View: Causal Inference | Maintainer: | Imke Mayer, Pan Zhao, Nick Huntington-Klein, Julie Josse | | Contact: | imke.
CRAN Task View: Mixed, Multilevel, and Hierarchical Models in R | Maintainer: | Ben Bolker, Julia Piaskowski, Emi Tanaka, Phillip Alday, Wolfgang Viechtbauer | | Contact: | bolker at mcmaster.
CRAN task views aim to provide guidance which packages on CRAN are relevant for tasks related to a certain topic.
First name: Last name: Username: Letters, digits and @/.
Provides a scrolling chat interface with multiline input, suitable for creating chatbot apps based on Large Language Models (LLMs). Designed to work particularly well with the ellmer R package for calling LLMs.
Step-by-step tutorials to put AI to work for you Click a topic to begin.
Contribute to marcosci/climate_multiples development by creating an account on GitHub.
Talk for useR!2018 in Brisbane: https://user2018.r-project.org by Jenny Bryan Twitter: https://twitter.com/jennyBryan/ GitHub: https://github.com/j…
Materials for rstudio::conf. Contribute to rstudio/rstudio-conf development by creating an account on GitHub.
Enseignements Chaires actuelles Les enseignements du Collège de France sont ouverts au public gratuitement et sans condition d'inscription, dans la limite des places disponibles.
By Jonas Kristoffer Lindeløv (blog, profile).
Compositional Visual Generation with Composable Diffusion Models
This site is powered by knitr and Jekyll. If you find any errors, please email winston@stdout.org
Illustration by Allison Horst Creating your personal website using Quarto What is Quarto? Quarto is a publishing system built on Pandoc that allows users to create dynamic content using R, Python, Julia, and ObservableJS (with plans to add more languages too!).
Hi there, and welcome! I am a behavioral research scientist and an instructor spcialized in psychology and statistics. I studied psychology at Université Grenoble Alpes and this is where I learnt how to use numbers (or so-called data science methods) to better understand human behavior. Right now, I
danknights has 23 repositories available. Follow their code on GitHub.
Statistician. Data scientist. Former academic cognitive scientist. Occasional generative artist. Evidently now also a pharmacometrician - djnavarro
Contribute to petergandenberger/dashboard-builder development by creating an account on GitHub.
A helpful 5-page machine learning cheatsheet to assist with exam reviews, interview prep, and anything in-between. - aaronwangy/Data-Science-Cheatsheet
This article will not be useful only for data scientists, programmers, mathematicians, statisticians, and other scientists, but also for everybody. This
The Pinterest of data visualization. Explore hundreds of stunning dataviz projects in a clean, organized layout. Easily searchable, filterable, and categorized by chart type for your convenience.
L’Institut Agro Rennes Angers Département Statistique et Informatique 65 rue de Saint-Brieuc CS 84215 35042 Rennes cedex, FRANCE david [dot] causeur [at] institut-agro [dot] fr +33 (0) 223 485 884 Researchgate Google scholar.
Test your regex by visualizing it with a live editor. JavaScript, Python, and PCRE.
Contribute to google-deepmind/educational development by creating an account on GitHub.
Deploying flexdashboard on Github Pages with Docker and Github Actions - RamiKrispin/deploy-flex-actions
A shiny application that enables the user to create a prototype UI, being able to drag and drop UI components before being able to save or download the equivalent R code.
Diffify provides you with a comparison between different versions of R packages stored on CRAN or Python packages stored on PyPI.
Dr Dominique Makowski's personal website with information, contact, publications and CV. Researching cognitive neuropsychology with a focus on reality bending.
The DrWhy.AI is the collection of tools for Explainable AI (XAI). Its based on principles and the grammar for exploration, explanation and visualisation of predictive models. This package is designed to make it easy to install and load multiple packages from the DrWhy.AI' universe.
Aide mémoire R Ce site est dédié à la programmation sous R.
Mike Mahoney PhD Student at SUNY-ESF and ESIP Community Fellow Focusing on visualization, VR and ML as ways to think about large-scale systems These slides: mm218.
Free, step-by-step course to learn machine learning... Get a world-class data science education without paying a dime!
Tired of typing the same sentences over and over? Discover the incredible power of a full-blown text expander.
Civil servants, public officials, and government bureaucrats swear an oath to serve in a democratic government, committing to acting in accordance with a set of values—including integrity, honesty, objectivity, loyalty, and stewardship—intended to uphold the public interest.
Des cours en ligne gratuits pour découvrir, apprendre, progresser et réussir avec des experts des meilleurs établissements d'enseignement supérieur.
FauxPilot - an open-source alternative to GitHub Copilot server - fauxpilot/fauxpilot
Adds an LLM-powered chatbot to your shiny app, that can turn your users' natural language questions into SQL queries that run against your data, and return the result as a reactive data frame. Use it to drive reactive calculations, visualizations, downloads, and more.
Slides for François Fleuret's Deep Learning Course
Figure 1: A time chart of logged events for two futures resolved by two parallel workers. This is a screenshot of Slide #18 in my talk. Below are the slides for my Futureverse: Profile Parallel Code talk that I presented at the useR! 2022 conference online and hosted by the Department of Biostatisti
Cours Python à destination des débutants 100% gratuit et interactif
G*Power Statistical Power Analyses for Mac and Windows G*Power is a tool to compute statistical power analyses for many different t tests, F tests, χ2 tests, z tests and some exact tests.
Le logiciel R est un environnement de programmation statistique et graphique largement utilisé par les chercheurs, les analystes de données et les statisticiens.
Software engineer for Shiny at @posit-pbc. gadenbuie has 329 repositories available. Follow their code on GitHub.
rstudio::conf-2022 2 day workshop on getting started with Quarto
Git is a free and open source distributed version control system designed to handle everything from small to very large projects with speed and efficiency.
GitHub Actions for the R community. Contribute to r-lib/actions development by creating an account on GitHub.
Follow this Hello World exercise to learn GitHub's pull request workflow.
Prettify your github profile using this amazing readme generator.
There are several ethical challenges facing text-to-image research broadly.
Research paper GitHub repository We introduce the Pathways Autoregressive Text-to-Image model (Parti), an autoregressive text-to-image generation model that achieves high-fidelity photorealistic image generation and supports content-rich synthesis involving complex compositions and world knowledge.
This workshop is a gentle introduction to Shiny and related concepts
The grammar of tables in python (pandas) and R (gt) Introduction The {ggplot2} 📦1is one of the most widely used packages for data visualization in R.
Choosing a statistical test This is chapter 37 of the first edition of Intuitive Biostatistics by Harvey Motulsky.
A half-a-day workshop with `R` and `Nimble`
Here you can find most of my recent presentations with related resources. If you would like to talk about these, my inbox is open!
Repository for the demos in the \"Hello, Quarto!\" talk - mine-cetinkaya-rundel/hello-quarto-demo
A visual explanation of multi-level modeling
Here at Hugging Face, we’re on a journey to advance and democratize ML for everyone. Along the way, we contribute to the development of technology for the better.
Apéro is a Hugo theme for personal websites. A Hugo theme you'll want to hang out with :milky_way: . This is the source for the theme files to install. - GitHub - hugo-apero/hugo-apero: Apéro i...
An official website of the United States government Here's how you know Official websites use.
A curated gallery celebrating data visualization as art. Discover innovative artworks from international artists who transform data into emotionally compelling visual experiences.
Introduction This website is an attempt to collect all the tutoring information I've created and put it in one place that can be accessed from anywhere with an internet connection.
| | | Ivan Laptev Professor at MBZUAI on leave from INRIA Paris Email: Ivan.
Hi, I am a research scientist at Meta Super Intelligence Labs working on post-training.
Assistant Professor in EMSE @ GWU; Engineering; Sustainability; Technology Innovation Policy; EVs; China; Data Science; Rstats; Python; Swing dancing - jhelvy
| I am currently on leave (“détachement”) to the Czech Technical University in Prague but keep close ties to the Willow team where I remain a close external collaborator.
Materials for rstudio::conf. Contribute to rstudio/rstudio-conf development by creating an account on GitHub.
Introduction à R et au tidyverse À propos de ce document Ce document est une introduction à R, logiciel libre de traitement et d’analyse de données.
Extension for Visual Studio Code - Automatically detect and resolve keybinding conflicts between VS Code extensions
Welcome to Mila Tea Talks! What are tea talks ? Tea talks are scientific keynote-like talks given at Mila on Friday mornings (10:30am EDT). We either have an internal or invited speaker give a ~1 hour talk with about 15 minutes of questions interspersed throughout. These talks are open to the
CV détaillé de Gourvès Laurent, Directeur de recherche CNRS à l'université Paris Dauphine-PSL. Retrouvez sa biographie, ses publications et ses coordonnées.
I am data scientist at the French national statistical institute, Insee.
M2 Mathématiques, Vision, Apprentissage Le MVA est un Master 2 Recherche créé en 1996, piloté par le département de mathématiques de l'ENS Paris-Saclay, co-accrédité avec l'Institut Polytechnique de Paris et partagé avec Université Paris Cité.
Today, we’re announcing that MCP Apps are now live as an official MCP extension. Tools can now return interactive UI components that render directly in the conversation: dashboards, forms, visualizations, multi-step workflows, and more. This is the first official MCP extension, and it’s ready for pr
Learn Machine Learning through understanding and doing!
Need Help Getting Started with Applied Machine Learning? These are the Step-by-Step Guides that You've Been Looking For! What do you want help with? Beginner Python Skills Understand ML Algorithms ML + Weka (no code) ML + Python (scikit-learn) ML + R (caret)…
:fire: Machine Learning Notebooks. Contribute to dair-ai/ML-Notebooks development by creating an account on GitHub.
My continuously updated Machine Learning, Probabilistic Models and Deep Learning notes and demos (2000+ slides) 我不间断更新的机器学习,概率模型和深度学习的讲义(2000+页)和视频链接 - roboticcam/machine-learning-notes
📺 Discover the latest machine learning / AI courses on YouTube. - dair-ai/ML-YouTube-Courses
A collection of resources to learn about MLOPs. Contribute to dair-ai/MLOPs-Primer development by creating an account on GitHub.
Contribute to isabelizimm/talk-rstudioconf2022-mlops development by creating an account on GitHub.
An introduction to the Random Forest algorithm.
Le MVA Le MVA (Mathématiques, Vision, Apprentissage), est un Master 2 Recherche créé en 1996 par Robert Azencott.
Ingénieure en science des données, PhD Département Statistique et informatique Unité pédagogique : Mathématiques appliquées Activités d'enseignement Enseignement numérique MOOC Analyse de données multidimensionnelles diffusé sur la plateforme France Université Numérique Cours-TD-TP - Analyse de donn
Learn how to make a great README for your programming project, and use the editable template to get started.
Hi there. I'm Malcolm. I'm a scientist and toolmaker. I teach open-source data science, make software, and analyze data. I've worked in academia and industry, including Posit, Teladoc Health, and Apple.
I am currently Associate Professor at ENSAI, on leave from Institut Agro Rennes Angers where I arrived in 2017.
Learn how to use Quarto CLI for your data science projects.
Math3ma is a blog about mathematics, maintained by Tai-Danae Bradley.
Matplotlib Tips and Demos¶ When I first learned Python three years ago, I was often finding myself having to lookup the same thing again and again for Matplotlib.
Maya Gans Data Visualization Engineer Biography I am currently a Data Visualization Engineer at Atorus Research where I develop custom applications using R and JavaScript.
It can be daunting to start using R when no one else in your office is! Using a case study from an administrative higher education office, learn how you can begin to build your own R ecosystem, step by step, to increase the efficiency and impact of your work, even as a solo contributor.
Models Demystified Deep Learning for Tabular Data: The Foundation Model Era deep learning machine learning boosting Uncertainty Estimation with Conformal Prediction machine learning regression boosting bayesian Imbalanced Outcomes machine learning regression boosting Deep Linear Models deep learning
I am a software engineer at Modal Labs, where I'm designing new abstractions for building data and AI applications in the cloud.
The book is based on Stanford Computer Science course CS246: Mining Massive Datasets (and CS345A: Data Mining).
Prise en main de l'environnement de programmation Cerise Diaporama de présentation pour la prise en main du RStudion workbench Cerise du MASA Version une journée L’ensemble des modules peuvent être suivis indépendamment les uns des autres.
Run AI models on NVIDIA GPUs in the cloud, data center, workstations, and PCs.
Naruto Hand Gesture Recognition with OpenCV and Transfer Learning - yaxan/Naruto_Handsign_Classification
RStudio Conf 2022 Links | Nick Strayer shinyuieditor gridlayout Slides Me.
https://njt-user-2022.netlify.app/#1. Contribute to njtierney/talk-user-2022 development by creating an account on GitHub.
Stay up-to-date on the latest data science and AI news in the worlds of artificial intelligence, machine learning, deep learning, implementation, and more.
Vous utilisez un navigateur obsolète, veuillez le mettre à jour.
News & Events A global hub for outstanding statistics research, teaching and advice Research Groups We feel enormous pride in the quality and the diversity of our research.
Visualizations for machine learning datasets. Contribute to PAIR-code/facets development by creating an account on GitHub.
On trouve ici des cours, exercices, TD avec le logiciel R, pour l'enseignement de la statistique et de l'analyse des données pour des biologistes.
The futurize() function transpiles calls to sequential map-reduce functions such as base::lapply(), purrr::map(), foreach::foreach() %do% { ... } into concurrent alternatives, providing you with a simple, straightforward path to scalable parallel computing via the future ecosystem <doi:10.32614/RJ-2
Découvrir le fonctionnement de R Aborder la dimension modulaire du logiciel S’approprier l’interface graphique du logiciel Être en capacité d’importer dans R un fichier CSV et de réaliser des calculs statistiques simples (somme, moyenne, table des fréquences) Être en capacité d’explorer les données,
Presentation slides for 'Tidy Finance with R' at useR!2022.
| Name | Last modified | Size | Description | | |---|---|---|---|---| | Parent Directory | - | ||| | 220talk.
Portfolio and Data Services. Power your business with automated data pipelines and carefully designed dashboards & apps.
a virtual hub at the interface of theoretical physics and deep learning.
regMMD - Robust Regression and Estimation Through MMD Minimization (written with Mathieu Gerber), doc MMDCopula - Estimation of Copula via MMD (written with Alexis Derumigny, Badr-Eddine Chérief-Abdellatif and Jean-David Fermanian), doc ISBF - Iterative Selection of Blocks of Features for regression
Scientific Software Engineer, Institut de Recherche Mathématique de Rennes, France. - pnavaro
A simple, interactive and fun playground to learn Docker Play with Docker (PWD) is a project hacked by Marcos Liljedhal and Jonathan Leibiusky and sponsored by Docker Inc.
Learn docker through online trainings in training.play-with-docker.com
Plotly ggplot2 Open Source Graphing Library With ggplotly() by Plotly, you can convert your ggplot2 figures into interactive ones powered by plotly.
A comprehensive guide to R package development using automation to tick checklists for documentation, exception handling, portability, code quality, and dependency management. Learn how to make your R packages sustainable and release-ready.
Programmer en R Apparence R est un langage de programmation dédié aux statistiques.
class: center, middle, inverse, title-slide # > 🏗 <br>> Project structure ### <br><br><b>Danielle Navarro</b> --- layout: true <div class=\"my-footer\"> <span> <a href=\"https://slides.
Learn data visualization in Python with PYTHON CHARTS! Create beautiful graphs step-by-step with matplotlib, seaborn and plotly with examples
Cheat Sheets Cheat sheets can be really helpful when you’re trying a set of exercises related to a specific topic, or working on a project.
Here is my personal list of legally free Python books. Warning: Packt free books are highly unreliable, what can be free today can no longer be free tomorrow Th...
| News and Announcements » | The QIIME tutorials illustrate how to use various features of QIIME.
A clone of schochastics-net with quarto. Emulates the hugo apero theme - schochastics/quarto-schochastics
Contribute to AlbertRapp/quarto_bottomup_blog development by creating an account on GitHub.
<- ggplot(diamonds, aes(x = cut, y = price, fill = cut)) + g geom_violin() + labs(title = \"Diamond price by cut\") Dark Mode Demo Toggle dark and light mode (there’s a switch in the upper right corner) to see the plot switch.
quarto demo with R code. Contribute to jeremy-allen/quarto-demo development by creating an account on GitHub.
https://raniere-phd.gitlab.io/quarto-document-template
With Shinylive, you can embed Shiny for Python applications into Quarto documents and run the entire application (including the Python runtime) inside the user’s web browser.
a11y fig-alt slide-tone image-alt image aria-label icon [[]{.
Learn R programming quickly with this comprehensive directory designed for both current R users and those transitioning from other statistical packages.
Learn R programming quickly with this comprehensive directory designed for both current R users and those transitioning from other statistical packages.
The Hitchhiker’s Guide to Responsible Machine Learning
People The community of people and research teams working on missing values is constantly growing but there are some researchers whose work can be considered as key contributions to the community and who provide a lot of material to different groups of interested people. Here we provide the links to
16 May 2022 A great way to learn how to analyze data or improve the skills you have is to watch experienced people do it. It’s handy if you have experienced colleagues around you, but what if your colleagues are too busy to help coach you, you’re still trying to …
Vous retrouverez ici toutes les lignes de code utilisées dans le livre.
Collection of utilities that improve using Databricks from R. Primarily functions that wrap specific Databricks APIs (<https://docs.databricks.com/api>), RStudio connection pane support, quality of life functions to make Databricks simpler to use.
The French version of this document is no longer maintained: be sure to check the more up-to-date English version.
The mcptools package enables apps like Claude Desktop, Claude Code, and VS Code GitHub Copilot to run R code using the Model Context Protocol (MCP).
You’re reading the first edition of R4DS; for the latest on this topic see the Dates and times chapter in the second edition. 16.1 Introduction This chapter will show you how to work with dates...
The conference is a scientifically & industry oriented, collegial event focused on the use of R in the development of pharmaceuticals.
R Workflow for Reproducible Data Analysis and Reporting
R Workflow for Reproducible Data Analysis and Reporting
Over 1000 topics to learn about any programming languages/software such as C#, Dapper, Entity Framework, SQL, and more!
Interested in our work? Want to become a Shiny wizard! Want to test ou tools? Want to know more about us? RinteRface aims at bringing the most famous open source HTML templates to R This 500+ full color pages book will give you all tools to become a Shiny UI master.
Easy web publishing from R Write R Markdown documents in RStudio.
rstudio::conf(2022, \"program\"). Contribute to rstudio/rstudio-conf-2022-program development by creating an account on GitHub.
Materials for rstudio::conf. Contribute to rstudio/rstudio-conf development by creating an account on GitHub.
A polyglot community of innovators and transformers. Learn, grow, and connect with a global community of data scientists at our annual data science conference.
Learning some topics in depth will both help you develop better code and share it more effectively with others.
Here are some common areas that people who already have some experience in R find particularly rewarding to learn.
Overview R packages are an ideal way to package and distribute R code and data for re-use by others. The RStudio IDE includes a variety of tools that make developing R packages easier and more prod...
Recommended Packages Many useful R function come in packages, free libraries of code written by R's active user community. To install an R package, open an R session and type at the command line in...
RegExr is an online tool to learn, build, & test Regular Expressions (RegEx / RegExp).
Regular expression tester with syntax highlighting, explanation, cheat sheet for PHP/PCRE, Python, GO, JavaScript, Java, C#/.NET, Rust.
Dans tout projet de Data Science, une étape INDISPENSABLE s’impose : la préparation des données.
Containers for machine learning. Contribute to replicate/cog development by creating an account on GitHub.
Provides tools for implementing Retrieval-Augmented Generation (RAG) workflows with Large Language Models (LLM). Includes functions for document processing, text chunking, embedding generation, storage management, and content retrieval. Supports various document types and embedding providers (Ollama
Row-oriented workflows in R with the tidyverse. Contribute to jennybc/row-oriented-workflows development by creating an account on GitHub.
This guide covers timeless ideas that are helpful to keep in mind while working with systems where performance matters.
STAT 545: Data wrangling, exploration, and analysis with R.
Ce site web contient les notes du cours STT-4230 / STT-6230 R pour scientifique, offert par le Département de mathématiques et de statistique de l’Université Laval (Québec, Canada).
In recent years RL has attracted a lot of attention due to the extremely impressive results that have been achieved in games such as Go As a way to teach myself about RL, a couple of years ago I built a simulator and trained an agent I ended up deciding that an interesting game to try would be \"Sett
Learning to play Settlers of Catan with Deep RL - custom training environment and implementation of PPO - henrycharlesworth/settlers_of_catan_RL
Introduction g6R can be easily integrated into Shiny applications using the g6_output() and render_g6() functions: library(shiny) library(g6R) library(bslib) nodes <- data.
Shiny is a package that makes it easy to create interactive web apps using R and Python.
Shiny is a package that makes it easy to create interactive web apps using R and Python.
Shiny is a package that makes it easy to create interactive web apps using R and Python.
Shiny Server Pro Admin Guide Getting Started Shiny Server enables users to host and manage Shiny applications on the Internet.
An interactive web application for demonstrating and using phyloseq. - joey711/shiny-phyloseq
ShinyProxy What is ShinyProxy? ShinyProxy is your favourite way to deploy data science apps in an enterprise context (Shiny, Dash, Streamlit, Jupyter notebooks, IDEs and more).
Best US online casinos for 2025—compare bonuses, payouts, crypto, and safety. Play real-money slots at trusted sites. 21+.
This program will bring together theoretical and applied researchers with the aim of understanding the complexity, optimization, and approximation questions underlying causal inference and discovery.
The gt package lets users easily format cells based on conditional statements about the rows. I'm looking for a way to format each cell based on the value in the cell. Here's what I mean. In the ta...
Enseignement Actuel Mon frère jumeau Afshine et moi avons eu la chance d'enseigner le cours CME 295: Transformers & Large Language Models à Stanford depuis le printemps 2025.
Teaching Current My twin brother Afshine and I have been lucky to teach the CME 295: Transformers & Large Language Models course at Stanford since Spring 2025.
A practical introduction to creating effective visualizations using ggplot2 A data science project workflow using RStudio and Make An introduction to geospatial data manipulation and visualization using R and Mapbox A collection of readings on data wrangling using the tidyverse A practical introduct
Performing groundbreaking Natural Language Processing research since 1999.
Statistical Rethinking course winter 2022. Contribute to rmcelreath/stat_rethinking_2022 development by creating an account on GitHub.
Introduction to the R programming language for beginners - What is R programming? - Pros & cons - Data manipulation - Graphics in R
This book contains both practical guides on exploring missing data, as well as some of the deeper details of how naniar works to help you better explore your missing data. A large component of this book are the exercises that accompany each section in each chapter.
Ce document a été généré directement depuis RStudio en utilisant l’outil Markdown.
Fine-tune neural translation models with mBART Jun 2020 by Tiago Ramalho mBART is another transformer model pretrained on so much data that no mortal would dare try to reproduce.
class: center, inverse, middle # Do you know the [{janitor}](https://github.
Transform yourself from a beginner to an advanced Tidyverse user with the help of this PDF-book. The book contains a collection of the most fascinating and useful Tidyverse tricks. I have been gathering all Tidyverse tricks I could find since June 2022 and compiled them into this singular resource.
R packages for data science The tidyverse is an opinionated collection of R packages designed for data science.
I procrastinated a deep dive into transformers for a few years.
As machine learning (ML) systems are increasingly being deployed in real-world applications, it is critical to ensure that these systems are behaving responsibly and are trustworthy.
At the heart of GitHub is an open-source version control system (VCS) called Git. Git is responsible for everything GitHub-related that happens locally on your computer.
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@Emil_Hvitfeldt: Are you using Quarto to create slides? Do you want to share your slides easily? Do you have minimal Github knowledge? If you answered yes to all 3 questions then read along in this 3...…
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Understanding statistics through interactive visualizations Statistical concepts can be difficult to understand from words and equations alone but understanding can come more easily if one gets to play with some numbers.
React is an open-source library designed to quickly develop user interfaces or UI components, on the front end. It has been developed by Facebook and the community (more than 1500 contributors)...
Apprenez à intégrer des applications Shiny interactives directement dans vos documents Quarto. Ce tutoriel aborde la configuration de l’extension Shinylive, la création d’une application Shiny autonome et la personnalisation des options du viewer.
With VERT, you can quickly convert any image, video, audio, and document file. No ads, no tracking, open source, and all processing (other than video) is done on your device.
Clone voices and generate speech with Qwen3-TTS
Willow team Willow is a joint team between Inria Paris, the computer science department of ENS Paris, and CNRS.
We work on open-source data projects and do education, consulting, and training in machine learning and statistics.
The page proposes links to the class material associated to the book Web Data Management, published by Cambdrige University Press in 2011.
Learn why thousands of companies rely on W&B as their system of record for training AI models and developing AI applications with confidence.
AI-driven development framework with specialized agents, guided workflows, and intelligent planning
I’m an entrepreneur and software developer focusing on analytical computing.
What They Forgot to Teach You About R The stuff you need to know about R, besides data analysis.
The AI powered GitHub and Gitlab app that explains the changes within your pull requests in plain english
Links: https://rstd.io/jenny-latinr Delivered at * Latin-R, http://latin-r.com, Buenos Aires 04-05 Sept 2018 * 10th Conference of the IASC-AR…
As a software developer or engineer, there is a magical feeling that comes from releasing open-source code. The feeling is a mix of terror and excitement. You’re eager to tell the world about your ...
Guide pour choisir un test statistique approprié en fonction de la situation Nous avons établi la grille ci-dessous pour vous guider dans le choix d’un test approprié en fonction de votre problématique et vos données. Le guide propose une formulation de l’hypothèse nulle et un exemple pour chaque si
This afternoon I will give a talk at the useR! 2022 conference on blogdown. Since I need to show a few live demos, I thought I’d better pre-record it just in case, which I did yesterday. If …
Leverage a personal AI search agent & customized recommendations with You.com's AI chatbot. Converse naturally and discover the power of AI. Chat now!
Meet Z.ai, your free AI-powered assistant. Build websites, create slides, analyze data, and get instant answers. Fast, smart, and reliable, powered by GLM-5.
Adaptive systems for evolving ideas – Zensical creates scalable Open Source systems for technical writing that always keep you in the flow
Materials for rstudio::conf. Contribute to rstudio/rstudio-conf development by creating an account on GitHub.
Premium, 100% Rust-based agent automation platform and visual control plane for the ZeroClaw Core Engine.
L’objet de l’AFIA est de promouvoir et de favoriser le développement de l’IA en France. A ce titre, si vous organisez un événement en France (conférence, atelier, école d’été), sur un ou plusieurs jours, lié à l’IA, vous êtes… Lire la suite
Posted by Sharan Narang and Aakanksha Chowdhery, Software Engineers, Google Research In recent years, large neural networks trained for language un...
Learn how to use R, {brms}, and {marginaleffects} to analyze conjoint data and find causal and descriptive quantities of interest, both frequentistly and Bayesianly
Define what marginal effects even are, and then explore the subtle differences between average marginal effects, marginal effects at the mean, and marginal effects at representative values with the marginaleffects and emmeans R packages
class: center, middle, inverse, title-slide # Lab 06: CS631 ## Making Slides in the Tada!-verse ### Alison Hill --- class: center, middle, inverse # First: ## Slides with `xaringan` -- # Second: ## Sites with `blogdown` --- background-image: url(\"https://media.
This is the site for sharing our Data Visualization Labs for CS631 at Oregon Health & Science University.
uv is an extremely fast Python package installer and resolver, designed as a drop-in alternative to pip and pip-tools.
Bayesian Thinking for Toddlers: The Cartoon For better or for worse, it appears that my most appreciated work is the children’s book Bayesian Thinking for Toddlers (the intro post is here and an exegesis is here).
Bayesian Causal Inference for Real World Interactive Systems
The objectives machine learning models optimize for do not always reflect the actual desiderata of the task at hand. Interpretability in models allows us to evaluate their decisions and obtain information that the objective alone cannot confer. Interpretability takes many forms and can be difficult
Ce blog n'a d'autre prétention que de me permettre de mettre à la disposition de tous des petits textes que j'écris.
Practical Statistics in Medicine with R 1st Edition Preface Whom is this textbook for? This textbook is based on my notes from a series of lectures given for a few years at the Aristotle University of Thessaloniki, Greece.
Explore how technical and social structures co-evolved over five centuries in this large-scale research visualization.
Artificial intelligence creates fantastic opportunities that can drastically increase the added value of your business.
My summary of the PyData Paris 2024 conference, held in late September
Closeread Closeread is a custom format for Quarto that enables scrollytelling features for HTML documents.
Editor’s Note: This post is part of our Next '23 series sharing the latest Google Maps Platform news from the global exhibition of inspiration, innovation, and education.
Neural Networks, Manifolds, and Topology Posted on April 6, 2014 topology, neural networks, deep learning, manifold hypothesisRecently, there’s been a great deal of excitement and interest in deep neural networks because they’ve achieved breakthrough results in areas such as computer vision.
Writing rough notes allows me share more content, since polishing takes lots of time.
Find all my posts about webR here. Note: the first post of this series explaining roughly what webR is, I won’t introduce it again here. Note 2: webR and the tools I’ve been writing are moving fast and if you’re reading this from the future, some of the things here might be obsolete.In this post, I’
A worlwide pioneer Launched in 2021, and funded by France 2030, Confiance.
Consensus is an AI academic search engine for peer-reviewed literature—your research OS for finding, organizing, and analyzing science 10x faster.
Let’s talk about version control and collaboration today and one of its powerful tools: git ✨ Using Git can be a lifesaver (and it has often been one in the past for me 🙏).
Built to make you extraordinarily productive, Cursor is the best way to build software with AI.
Research My research interests include machine learning for computer vision.
Discover 6 open source development projects that you can self-host.
DevOps for Data Science Welcome! In this book, you’ll learn about DevOps conventions, tools, and practices that can be useful to you as a data scientist.
A toolbox for production-ready data science Get started Introduction to Kedro Learn what Kedro is, why it exists, and how it can help.
Gain control with LangGraph to design agents that reliably handle complex tasks
dplyr tutorial What is dplyr? dplyr is a powerful R-package to transform and summarize tabular data with rows and columns.
Dynalist lets you organize your ideas and tasks in simple lists. It's powerful, yet easy to use. Try the live demo now, no need to sign up.
This vignette can be referred to by citing the following: Makowski, D.
Learn R Here are some links to get started with R: R for Datascience YaRrr! The Pirate’s Guide to R Yan Holtz’s tutorials The Tidynomicon: A Brief Introduction to R for Python Programmers Quick-R EdX courses LearnR Youtube Channel Stay tuned Here are some links of blogs and such to keep in touch wit
ISLR tidymodels labs 1 Introduction This book aims to be a complement to the 2nd edition An Introduction to Statistical Learning book with translations of the labs into using the tidymodels set of packages.
Having fun with iFrames In Quarto Presentations one way to add something extra is to use Slide Backgrounds Images and videos are good for some added flair, and they automatically fill the background Using html elements and javascript to make an animated background, is almost impossible to get right
library(MASS) # For Boston data set library(tidymodels) library(ISLR) 3 Linear Regression This lab will go over how to perform linear regression.
Combine research design, causal inference, and econometric tools to measure the effects of social programs
Format for converting an R Markdown document to a grid oriented dashboard. The dashboard flexibly adapts the size of it's components to the containing web page.
Une plateforme intuitive pour apprendre à coder, découvrir les sciences et s’initier à l’intelligence artificielle (IA) avec Arduino, Python, micro:bit et plus.
Hire me I’m looking for my next role, if you are (or know someone who is) recruiting, you will find below my resume, a short “About me”, and a longer version of my skills and accomplishments.
Smash is a fast, secure, smooth and sustainable service to transfer your (extra) large files. Use it for free or unlock enhanced features with premium plans.
Welcome to geocompx! Here you will find content, including books and beyond, on reproducible geographic data analysis, modeling, and visualization with open source software.
ggplot2 plotting related files. Contribute to claragranell/ggplot2 development by creating an account on GitHub.
Inspired by [Henry Wang](https://twitter.com/henrywangnl)❜s ❝[ggplot2 Theme Elements Demonstration](https://henrywang.nl/ggplot2-theme-elements-demonstration/)❞, I created one for myself displaying all of the elements I frequently use and always google. Feel free to download and use it as well!
ggsql is still in early development and all functionality are subject to change A declarative visualization language that extends SQL with powerful data visualization capabilities.
Git repositories with educational materials for the computational life sciences
An example app for illustrating golem features. Contribute to ColinFay/golemexample development by creating an account on GitHub.
A Framework for Building Robust Shiny Apps . Contribute to ThinkR-open/golem development by creating an account on GitHub.
Cleaning data can take hundreds or thousands of lines.
Run open-source AI models locally on your device. GPT4All delivers private, high-performance AI with no cloud required—your data stays on your machine.
Plotly allows you to easily translate your ggplot2 graphics to an interactive web-based version, and also provides bindings to the plotly.
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
There are a number of learners in the Intro to R course I’m teaching at Fred Hutch that are coming to R from SAS.
Learn how to build a serverless Shiny app with webR: a package that allows you to run R completely on the user's machine without an R server
Shiny and Quarto help R and Python users build powerful, interactive web apps and high-quality documents.
indiedown makes it easy to generate a customized R Markdown PDF template that follow the principles of your corporate design.
Learn how to apply the DRY (Don't Repeat Yourself) principle to R package development. Covers documentation, vignette setup, unit testing, data management, dependency management, and exception handling to make your R packages more maintainable.
Learn how to apply the DRY (Don't Repeat Yourself) principle to R package development. Covers documentation, vignette setup, unit testing, data management, dependency management, and exception handling to make your R packages more maintainable.
Maîtrisez la gouvernance de vos données avec un cloud indépendant. Des solutions hébergées au cœur de l’Europe, conçues pour protéger votre confidentialité.
Get interior design ideas using artificial intelligence and virtually stage interiors for real estate listings with different interior styles. Take a picture of a room and instantly redesign it with AI. Upload a photo of your interior and transform it completely. Instantly redesign, furnish, reimagi
Our new X account is live! Follow @wizwand_team for updates Search any task Feedback Search any task SOTA Knowledge Graph Completion benchmarks and papers with code | Wizwand Our new X account is live! Follow @wizwand_team for updates Home / Tasks Knowledge Graph Completion Benchmarks Dataset Name S
Welcome Course description The objective of this course is to show students how statistics is used in practice to answer a specific question, by introducing a series of important model-based approaches.
2020 - first place¶ 2020 - second place¶ 2020 - third place¶ 2020 - honorable mention¶ 2019 - first place¶ 2019 - second place¶ 2019 - third place¶ 2019 - Honorable mention¶ 2018 - first place¶ 2018 - second place¶ 2018 - third place¶ 2018 - honorable mention¶ 2015 - first place¶ 2015 - second place
0 Skip to Content jiddu alexander R & Shiny SVG input generator Junction profiling Scrollytelling & D3js Fossil CO₂ emissions Traffic accidents in Dutch provinces Global Warming Global and National Greenhouse Gases Emissions Open Menu Close Menu jiddu alexander R & Shiny SVG input generator Junction
Reimert et al., (2024). extendr: Frictionless bindings for R and Rust. Journal of Open Source Software, 9(99), 6394, https://doi.org/10.21105/joss.06394
Are you an R user considering switching from R Markdown to Quarto? Here are our favourite features that we think R users might benefit from.
Données des entreprises Décisions de justice Dépôt d'annonces légales & formalités entreprises Données immobilières Information institutionnelle Données des entreprises internationales Retrouvez toutes vos décisions de justice, textes de loi et commentaires juridiques centralisés au sein de notre pl
Contribute to jbkunst/klassets development by creating an account on GitHub.
Vous en avez assez de passer des heures à retranscrire à la main vos vidéos YouTube ? Ou peut-être cherchez-vous un moyen efficace de transformer vos ...
Dashboards are great for data snapshots--but what if you need something more agile in R? — Marc J.
Materials for rstudio::conf. Contribute to rstudio/rstudio-conf development by creating an account on GitHub.
An interactive Git visualization tool to educate and challenge!
L’extension CookieViz offre des fonctionalités similaires au logiciel déjà publié et récompensé au Global Privacy and Data Protection Awards en 2021.
Makes learning, teaching and debugging iterator functions from the purrr package easy by translating them into regular for loops.
Tutorial In this tutorial we will wrap a version of the guessing game from The Rust Book to run in Python using pyo3.
How to use Mixed models to Estimate Individuals' Scores Source:vignettes/estimate_grouplevel.
An open-source and fully-reproducible electronic textbook for teaching statistical inference using tidyverse data science tools.
Typst or LaTeX? Styling PDF documents with Quarto extensions Nicola Rennie, Lancaster University satRdays London, 27 April 2024 Academic background in statistics and operational research.
When adding JavaScript to your data work, it can be useful to see how it compares with other languages you’ve used before. Here, we show common data wrangling methods (like filtering, sorting, and adding columns) in JavaScript, Python, SQL, R, and Excel. All examples use the mock data below, stored
Continue enables you to easily create your own coding assistant directly inside Visual Studio Code and JetBrains with open-source LLMs.
An open textbook for Biological Psychology undergraduate students.
Run AI on your own terms. Connect any model, extend with code, protect what matters—without compromise.
Pastum (VS Code extension) allows you to quickly transform any text table from your clipboard into a dataframe object in your favorite language — R, Python, Julia, JavaScript or even Markdown.
Jump to: Quick Intro, Themes, Theme Settings, Fonts, Colors, Adding Custom CSS Quick Intro First, add the xaringan-themer.
Give your xaringan slides some style with xaringanthemer. Easy slide and plot themes for xaringan slides.
You can integrate mathematical expressions using AsciiMath format. Useful for demonstration or algorithm details.
Tinker with a real neural network right here in your browser.
Meet the winners of the Shiny Contest. With over 100 submissions across a wide range of topics, check out the best Shiny apps we've seen this year.
This is a version of a talk I gave for posit::conf(2024).
Bring Quarto to life with {webR} Quarto can be frustrating: you read a report, but cannot interact with it! You're browser doesn't speak R,so there is nothing you can change.
Psychologists from @UofGPsychNeuro advocating open, reproducible methods teaching.
Shiny helps R and Python users build powerful, interactive web apps.
map() This work is licensed under a Creative Commons Attribution-ShareAlike 4.
Slides to complement a hands-on workshop on the R package purrr (https://purrr.tidyverse.org)
I have been writing Python for 14 years next month. When I started, people were still using easy_install to install egg-based packages for Python 2.7 and nobody had heard about Conda yet, much less uv. The Python tool ecosystem has changed since. Many people are confused by the fragmentation in the
Most medium to large programs are organized into modules. This way, it becomes possible to logically separate various parts of a program based on thei
Cette partie du cours introduit le traitement automatique du langage (NLP), un domaine scientifique à la croisée de la linguistique et des statistiques devenu, du fait de l’engouement envers les IA génératives, central dans le domaine de la data science. A travers des exemples littéraires, dcette pa
Abstract I present a method for reactively updating a table of acronyms from a Shiny interactive timeline using renderDataTable and timevis. The method is used in the new Shiny app, stratvis. The stratvis app The stratvis Shiny app provides a rich a...
Visual Diagnostic Tools for Causal Inference Here we are going to look at several… Aug 4, 2023 Welcome to the Causal Inference in R Blog! Here you’ll find more information about our packages, book, courses, and other information about causal inference.
Explore the documentation of all R packages available, including functions and datasets
A dropdown R or Python console Throughout this presentation, an interactive R console and editor can be invoked by pressing the drop shortcut By default, the drop shortcut is the backtick key: ` Alternatively, click the console button in the bottom left of the slide Set the drop shortcut and button
rOpenSci fosters a culture of open and reproducible research using shared data and reusable software.
Building reproducible analytical pipelines with R Welcome! How using a few ideas from software engineering can help data scientists, analysts and researchers write reliable code Data scientists, statisticians, analysts, researchers, and many other professionals write a lot of code.
Purrr is the tidyverse’s answer to apply functions for iteration. It’s one of those packages that you might have heard of, but seemed too complicated to sit down and learn. Starting with map functions, and taking you on a journey that will harness the power of the list, this post will have you purrr
Commonly used character classes and regular expressions. These shortcuts are substituted inside rex calls.
The R Installation Manager. Contribute to r-lib/rig development by creating an account on GitHub.
Data-masking functions require special programming patterns when used inside other functions. In this topic we'll review and compare the different patterns that can be used to solve specific problems. If you are a beginner, you might want to start with one of these tutorials: Programming with dplyr
Data-masking is a distinctive feature of R whereby programming is performed directly on a data set, with columns defined as normal objects. # Unmasked programming mean(mtcars$cyl + mtcars$am) #> [1] 6.59375 # Referring to columns is an error - Where is the data? mean(cyl + am) #> Error: #> ! object
Community driven roadmaps, articles and guides for developers to grow in their career.
Automate your browser actions LISER February 22, 2023 Do you really need scraping? Before scraping: is there an API? Scraping can be divided in two steps: These 2 steps don’t necessarily require the same tools, and shouldn’t be carried out at the same time.
Materials for rstudio::conf. Contribute to rstudio/rstudio-conf development by creating an account on GitHub.
How can I download all issues information from Gitlab or Github and create a summary report of my commit messages for my client?
Many R package authors (including myself) lump a collection of small, useful functions into some type of utils.R file and usually do not export the functions since they are (generally) designed to work on package internals rather than expose their functionality via the exported package API. Just lik
Gradient descent is the preferred way to optimize neural networks and many other machine learning algorithms but is often used as a black box. This post explores how many of the most popular gradient-based optimization algorithms such as Momentum, Adagrad, and Adam actually work.
Find R packages by what they do Search 23,000+ packages from CRAN, Bioconductor, and GitHub.
About Me I completed my PhD in biostatistics1 at the University of Hohenheim in 2019 and have since been working at BioMath, where I am now Managing Director.
Shiny app as R package to analyze Twitter sentiment - jiwanheo/senTWEETment
Shiny is a package that makes it easy to create interactive web apps using R and Python.
shinydashboard makes it easy to use Shiny to create dashboards like these: Dashboard Bus dashboard Get started.
rstudio::conf(2022) - {shinytest2}. Contribute to schloerke/presentation-2022-07-28-rstudioconf22-shinytest2 development by creating an account on GitHub.
Logiciel open source sans limite d'utilisation - convertisseur tous formats codecs professionnels et standards
Situations in which PDP, ALE, LIME, LOCO and feature importance fail.
In standard data-science practice, a significant effort is spent on preparing the data before statistical learning. One reason is that the data come fro…
Le logiciel R est un environnement de programmation statistique et graphique largement utilisé par les chercheurs, les analystes de données et les statisticiens.
Quelques jours d'exploration de VSCode après de nombreuses années à développer avec RStudio
Quelques jours d'exploration de VSCode après de nombreuses années à développer avec RStudio
Statistical Analyses - Data Analysis Examples - Textbook Examples (see also Stat Books for Loan on R) - Downloadable Books on R Important Links - How can I get R? Where can I run R? - Installing, Customizing, Updating R - Documentation for R packages organized by topical domains Have you seen? - Cla
Schedule and course materials for Statistical Computing (JHSPH Biostatistics 140.776 Fall 2022).
Schedule and course materials for Statistical Programming Paradigms and Workflows (JHSPH Biostatistics 140.840 Fall 2022).
Découvrez des résumés rapides alimentés par l'IA des vidéos YouTube sur Summarize.ing. Accédez aux points forts, aux cartes mentales et aux résumés segmentés en moins d'une minute. Gagnez du temps, maîtrisez l'essentiel sans effort !
Currently, it is hard to reap the benefits of deep learning for Bayesian methods, which allow the explicit specification of prior knowledge and accurately capture model uncertainty. We present...
Explore Taipy Designer, the cutting-edge drag-and-drop GUI builder designed for Python developers. Create dynamic GUIs effortlessly with a WYSIWYG environment. Connect widgets to your Python variables, style graphics with ease, and focus on results with our sophisticated yet convenient editor. Reque
Tanya Shapiro Home About Talks Blog Projects Talks Categories All (7) Observable (1) Python (1) Quarto (1) R (5) data visualization (6) gganimate (1) ggplot2 (3) plotnine (1) reactable (1) tables (1) Intro to Observable Plot This is an introductory code walk-thru with Observable Plot.
Telling Stories with Data With Applications in R and Python Endorsements This clean and fun book covers a wide range of topics on statistical communication, programming, and modeling in a way that should be a useful supplement to any statistics course or self-learning program.
Reading material: The tidy modeling book The tidymodels blog on conformal regression The notes of Angelopoulos The notes of Tibshirani The book of Christoph Molnar The book of Valeriy Manokhin The package of Sussman et al. Getting some data We will look at Indian trade data hosted on Kaggle for …
A broad overview of the sub-field of machine learning interpretability; conceptual frameworks, existing research, and future directions.
La version 0.3.3 de golem est disponible sur le CRAN, elle propose une nouvelle approche de construction d'images docker pour le déploiement de vos
Streamlines the creation of common charts by taking care of a lot of data preprocessing and plot customization for the user. Provides a high-level interface for creating plots using ggplot2.
An opinionated approach on empirical research in financial economics
Unlock lifetime access to Reactive Web Dashboards with Shiny for free, learn at your own pace, and start building real Python projects on Talk Python Training.
A book about deeply customizing Shiny app for production.
Slides https://agstn.github.io/UseR2022_dashboards/UseR2022_dashboards.html - agstn/UseR2022_dashboards
Inspiration Exchange is a series of engagement sessions aiming to share ideas and discuss the future of machine learning in healthcare.
What? tinytable is a small but powerful R package to draw beautiful tables in a variety of formats: HTML, LaTeX, Word1, PDF, PNG, Markdown, and Typst.
Implementation of Reinforcement Learning with Human Feedback for text summarization task using CarperAI's trlX framework. Made by Ayush Thakur using W&B
Download webrios by James Balamuta on the App Store. See screenshots, ratings and reviews, user tips, and more apps like webrios.
A repository of high-quality, cited, automatically generated scientific articles using PaperQA by FutureHouse.
As a software developer or engineer, there is a magical feeling that comes from releasing open-source code. The feeling is a mix of terror and excitement. You’re eager to tell the world about your ...
2022 has come and gone and we’ve learned a lot about how the brain is – or isn’t – like an artificial neural network. There isn’t a single journal or venue that focuses exclusively on neuroAI so th…
Imagine that you are taken with a sudden desire to understand how the fruit of a tropical tree gets transformed into chocolate bars, or want to understand the role of fever in the human body's immune response: how would you go about finding that information? If your specific question has already bee
Zed is a high-performance, multiplayer code editor from the creators of Atom and Tree-sitter.
This workshop will bring together leaders from academia and industry to showcase recent methodological advances of Graph Neural Networks, a wide range of applications to different domains as well as machine learning frameworks and practical challenges for large-scale training and deployment of graph
Want to add a resource? Edit data/resources.txt and open a PR on GitHub. Each resource is a small YAML block:
---
title: "Resource Title"
type: Book
link: https://example.com
language: R
category: "Statistics;Tutorial"
description: "A brief one-sentence description shown on hover and in search."
---The description field is optional but recommended — it powers the hover tooltip on each card title and is included in the full-text search.
See CONTRIBUTING.md for the full guide, including the automated workflow for adding resources via Google Keep.
Links to external websites are provided for convenience and informational purposes only.