Implement a ChatGPT-like LLM in PyTorch from scratch, step by step
- gpt
- large-language-models
- llm
- python
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Implement a ChatGPT-like LLM in PyTorch from scratch, step by step
⛔️ DEPRECATED – See https://github.com/ageron/handson-ml3 or handson-mlp instead.
⛔️ DEPRECATED – See https://github.com/ageron/handson-ml3 or handson-mlp instead.
Code for Machine Learning for Trading, 3rd edition — from data sourcing to live execution.
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.
[WIP] Resources for AI engineers. Also contains supporting materials for the book AI Engineering (Chip Huyen, 2025)
Translated"Lee Hung-yi's Deep Learning Tutorial" (recommended by Professor Hung-yi Lee 👍, the Apple Book 🍎), PDF download address: https://github.com/datawhalechina/leedl-tutorial/releases
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
TranslatedOpen source Deep Learning book, based on TensorFlow 2.0 framework.
PyTorch tutorials and fun projects including neural talk, neural style, poem writing, anime generation (《深度学习框架PyTorch:入门与实战》)
《Python Cookbook》 3rd Edition Translation
The "Python Machine Learning (2nd edition)" book code repository and info resource
Python code for "Probabilistic Machine learning" book by Kevin Murphy
Code for Tensorflow Machine Learning Cookbook
T81-558: Keras - Applications of Deep Neural Networks @Washington University in St. Louis
Code for the book Deep Learning with PyTorch by Eli Stevens, Luca Antiga, and Thomas Viehmann.
The "Python Machine Learning (3rd edition)" book code repository
Jupyter notebooks for the Natural Language Processing with Transformers book
Translated"PyTorch Practical Tutorial" (Second Edition): whether you are starting from zero, working on CV, NLP, or LLM project applications, or moving on to advanced engineering deployment, it's all here. We believe that with the help of this book, readers will be able to master the use of PyTorch with ease and become an excellent deep learning engineer.
Accompanying source code for Machine Learning with TensorFlow. Refer to the book for step-by-step explanations.
Build a modern LLM from scratch. Every line commented. Explained like we are five.
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简单粗暴 TensorFlow 2 | A Concise Handbook of TensorFlow 2 | 一本简明的 TensorFlow 2 入门指导教程
本项目将《动手学深度学习》(Dive into Deep Learning)原书中的MXNet实现改为TensorFlow 2.0实现,项目已得到李沐老师的认可