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Streamlit — The fastest way to build data apps in Python - GitHub - streamlit/streamlit: Streamlit — The fastest way to build data apps in Python

In-person registration is now open for posit::conf(2023), happening September 17-20 in Chicago, IL!

Tidy data structures, summaries, and visualisations for missing data - GitHub - njtierney/naniar: Tidy data structures, summaries, and visualisations for missing data

User-Friendly R Package for Supervised Machine Learning Pipelines - GitHub - SchlossLab/mikropml: User-Friendly R Package for Supervised Machine Learning Pipelines

Stephen Wolfram explores the broader picture of what's going on inside ChatGPT and why it produces meaningful text. Discusses models, training neural nets, embeddings, tokens, transformers, language syntax.

When I first started programming, I clearly remember feeling I had to add comments, that would repeat exactly what the code below was doing, as if it were the script for some sort of voice over. I want you to know like I now do that it’s not the way to comment one’s code. 😅 An important goal of good code is to be readable so that future contributors can build with and upon it as needed.

How support for rtweet will continue going forward.

Dynamite is a new R package for Bayesian modelling of complex panel data using dynamic multivariate panel models.

Maybe you’re an engineer creating a new machine vision system to track birds. You might be a journalist using social media data to research Costa Rican households. You could be a researcher who stumbled upon your university’s archive of handwritten census cards from 1939. Or a designer creating a chatbot that relies on large language models like GPT-3. Perhaps you’re an artist experimenting with visual style combinations using DALLE-2. Or maybe you’re an activist with an urgent story that needs telling, and you’re searching for the right dataset to tell it.

The turn-of-the-century literary canon, using data from college syllabi

Weekly bite-sized tips on DataViz, Shiny and Stats/Machine Learning.

1. Learn broadly. 2. Learn deeply. 3. Don't be afraid to re-learn

Bar charts are easy to make but hard to perfect. Let's create a small checklist to make things easier.

This blog post is an in-depth guide on how to start blogging with Quarto.

I held a short workshop teaching R to Economics students. Here are six things that I wish I had known in advance.

Using concepts like dot-dot-dot and curly-curly we create functions that are more versatile and can be used in multiple settings.

Training neural networks can be very confusing! What’s a good learning rate? How many hidden layers should your network have? Is dropout actually useful? Why are your gradients vanishing? In this p…

The part art, part science of picking the perfect machine learning model. The number of shiny models out there can be overwhelming, which means a lot of times people fallback on a few they trust th…

Company researchers explain what’s needed to emulate a great tutor.

My personal notes from machine learning class. These notes will continue to be updated and improved as I continue to review the course to…

Based off of PythonInR (https://bitbucket.org/Floooo/pythoninr/) but includes a standalone, compiled from source python instead of relying on the python installed on the host machine - haozhu233/Py...

🌙🦉 An RStudio, tmThemes, and Ace editor adaptation of @sdras' Night Owl VS Code theme… - GitHub - batpigandme/night-owlish: 🌙🦉 An RStudio, tmThemes, and Ace editor adaptation of @sdras&...

Contribute to haozhu233/ezsummary development by creating an account on GitHub.

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 example, you will learn how to dynamically create content from R code, reference code in other documents or chunks, control the formatting with customer templates, fine-tune how your code is processed, and incorporate multiple languages into your analysis.

jQuery Sparkline HTML Widget for R. Contribute to htmlwidgets/sparkline development by creating an account on GitHub.

LaTeX Journal Article Templates for R Markdown. Contribute to rstudio/rticles development by creating an account on GitHub.

R client for various CrossRef APIs. Contribute to ropensci/rcrossref development by creating an account on GitHub.