Stars
Implement a ChatGPT-like LLM in PyTorch from scratch, step by step
Learn how to develop, deploy and iterate on production-grade ML applications.
This is a repo with links to everything you'd ever want to learn about data engineering
Data Engineering Zoomcamp is a free 9-week course on building production-ready data pipelines. The next cohort starts in January 2026. Join the course here 👇🏼
⛔️ DEPRECATED – See https://github.com/ageron/handson-ml3 or handson-mlp instead.
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 ;)
Python programs, usually short, of considerable difficulty, to perfect particular skills.
The repository provides code for running inference with the Meta Segment Anything Model 2 (SAM 2), links for downloading the trained model checkpoints, and example notebooks that show how to use th…
Materials for the Learn PyTorch for Deep Learning: Zero to Mastery course.
Data and code behind the articles and graphics at FiveThirtyEight
Learn ML engineering for free in 4 months! Register here 👇🏼
Practice your pandas skills!
Free online textbook of Jupyter notebooks for fast.ai Computational Linear Algebra course
This repo is meant to serve as a guide for Machine Learning/AI technical interviews.
Playing Pokemon Red with Reinforcement Learning
Repository to store sample python programs for python learning
Recipes for using Python's pandas library
Collection of notebooks about quantitative finance, with interactive python code.
Notebooks for learning deep learning
"Probabilistic Machine Learning" - a book series by Kevin Murphy
Notebooks using the Hugging Face libraries 🤗
Solve puzzles. Improve your pytorch.
The Jupyter Notebooks behind my OReilly report, "A Whirlwind Tour of Python"
NMA Computational Neuroscience course
100 data puzzles for pandas, ranging from short and simple to super tricky (60% complete)
📊⚽ A collection of football analytics projects, data, and analysis by Edd Webster (@eddwebster), including a curated list of publicly available resources published by the football analytics community.
Course materials and handouts for #100DaysOfCode in Python course
PyMC educational resources