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TranslatedHello Algo (《Hello 算法》): An animated, illustrated data structures and algorithms tutorial with one-click code running. Supports Simplified Chinese, Traditional Chinese, English, and Japanese, and provides code implementations in Python, Java, C++, C, C#, JS, Go, Swift, Rust, Ruby, Kotlin, TS, Dart, and more
Implement a ChatGPT-like LLM in PyTorch from scratch, step by step
Translated《动手学深度学习》 (Dive into Deep Learning): for Chinese readers, runnable, and open to discussion. The Chinese and English editions are used for teaching at more than 500 universities in more than 70 countries.
Python Data Science Handbook: full text in Jupyter Notebooks
A book-in-progress about the Linux kernel and its insides.
Python sample codes and textbook for robotics algorithms.
Official code repo for the O'Reilly Book - "Hands-On Large Language Models"
Machine Learning Systems: Foundations, Scaling, Agentic AI, and Physical AI (Vols I–IV) • Harvard CS249r | https://mlsysbook.ai
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
⛔️ DEPRECATED – See https://github.com/ageron/handson-ml3 or handson-mlp instead.
Python best practices guidebook, written for humans.
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 ;)
⛔️ DEPRECATED – See https://github.com/ageron/handson-ml3 or handson-mlp instead.
The fastai book, published as Jupyter Notebooks
Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media
TranslatedChinese translation of 《Designing Data-Intensive Application》 (DDIA), 1st edition / 2nd edition
Code for Machine Learning for Trading, 3rd edition — from data sourcing to live execution.
TranslatedThe pytorch handbook is an open-source book that aims to help friends who want to use PyTorch for deep learning development and research get started quickly. All of the PyTorch tutorials it contains have been tested to ensure they run successfully.
Jupyter notebooks for the code samples of the book "Deep Learning with Python"
Machine Learning Engineering Open Book
TranslatedCode implementation of 《统计学习方法》 (Statistical Learning Methods)
TranslatedThis project changes the MXNet implementations in the original book 《动手学深度学习》 (Dive into Deep Learning) into PyTorch implementations.
Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises include solutions.
One has no future if one couldn't teach themself.