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Python - 100天从新手到大师
Python Data Science Handbook: full text in Jupyter Notebooks
Learn how to design, develop, deploy and iterate on production-grade ML applications.
TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)
Google Research
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 instead.
A game theoretic approach to explain the output of any machine learning model.
Python programs, usually short, of considerable difficulty, to perfect particular skills.
🤖 Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained
100-Days-Of-ML-Code中文版
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 filte…
💿 Free software that works great, and also happens to be open-source Python.
A collection of various deep learning architectures, models, and tips
Data and code behind the articles and graphics at FiveThirtyEight
📡 Simple and ready-to-use tutorials for TensorFlow
A tiny scalar-valued autograd engine and a neural net library on top of it with PyTorch-like API
Dopamine is a research framework for fast prototyping of reinforcement learning algorithms.
Tutorials, assignments, and competitions for MIT Deep Learning related courses.
Python implementation of algorithms from Russell And Norvig's "Artificial Intelligence - A Modern Approach"
Notebooks and code for the book "Introduction to Machine Learning with Python"
Implementation of Dreambooth (https://arxiv.org/abs/2208.12242) with Stable Diffusion
Playing Pokemon Red with Reinforcement Learning
A curated list of applied machine learning and data science notebooks and libraries across different industries (by @firmai)
An adversarial example library for constructing attacks, building defenses, and benchmarking both
TensorFlow 2.x version's Tutorials and Examples, including CNN, RNN, GAN, Auto-Encoders, FasterRCNN, GPT, BERT examples, etc. TF 2.0版入门实例代码，实战教程。
A course in reinforcement learning in the wild
Python assignments for the machine learning class by andrew ng on coursera with complete submission for grading capability and re-written instructions.