CMU Lecture: Machine Learning In Production / AI Engineering / Software Engineering for AI-Enabled Systems (SE4AI)

A Python Interpreter written in Rust

📋 Survey papers summarizing advances in deep learning, NLP, CV, graphs, reinforcement learning, recommendations, graphs, etc.

Comprehensive collection of programming styles using a simple computational task, term frequency

CLI and local web plain text note‑taking, bookmarking, and archiving with linking, tagging, filtering, search, Git versioning & syncing, Pandoc conversion, + more, in a single portable script.

The Learning Interpretability Tool: Interactively analyze ML models to understand their behavior in an extensible and framework agnostic interface.

📡📝 A GitHub Action that updates a section of a README from an RSS feed.

Data augmentation for NLP

YSDA course in Natural Language Processing

The website for the CMU Language Technologies Institute low resource NLP bootcamp 2020

Translations of TensorFlow documentation

📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.

Extract data from a wide range of Internet sources into a pandas DataFrame.

Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more

Reading list for research topics in multimodal machine learning

A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning

Always know what to expect from your data.

I am trying to describe complex matters in simple doodles!

cuDF - GPU DataFrame Library

Free to use online tool for labelling photos. https://makesense.ai

This is a meta repo to collect Global Diversity CFP Day Jakarta 2020

Image augmentation for machine learning experiments.

Pytorch implementation of MixNMatch

An Introduction to Statistical Learning (James, Witten, Hastie, Tibshirani, 2013): Python code

Text and supporting code for Think Stats, 2nd Edition

A curated list of awesome self-supervised methods

aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)

A probabilistic programming language in TensorFlow. Deep generative models, variational inference.

😈Awful AI is a curated list to track current scary usages of AI - hoping to raise awareness