ShusenTang/Dive-into-DL-PyTorch Alternatives

choose for a practical fastai-based deep-learning course with notebooks if you prefer high-level APIs over PyTorch-from-scratch

The fastai book, published as Jupyter Notebooks

choose for a broad Chinese AI/ML/DL tutorial collection spanning several frameworks if you want more than D2L

AiLearning：数据分析+机器学习实战+线性代数+PyTorch+NLTK+TF2

choose for a TensorFlow 2.0 version of D2L, though it is unmaintained

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

choose for the official English multi-framework D2L book (PyTorch/TF/JAX) rather than the Chinese PyTorch-only adaptation

Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.

choose for code-first implementation of GPT-like LLMs in PyTorch, but it is much narrower than D2L's breadth

Implement a ChatGPT-like LLM in PyTorch from scratch, step by step

choose for a focused LLM-foundations book, but it lacks D2L's general DL and hands-on notebook breadth

A book for Learning the Foundations of LLMs

stale PyTorch adaptation of the same D2L book; only useful if you want that older snapshot

This project reproduces the book Dive Into Deep Learning (https://d2l.ai/), adapting the code from MXNet into PyTorch.

quick personal DL notes/notebooks, less structured and less comprehensive than D2L

Personal deep learning study notes and tutorial-style notebooks

classic Stanford UFLDL tutorial, a pre-PyTorch generation of deep-learning teaching

Stanford Unsupervised Feature Learning and Deep Learning Tutorial

older Vietnamese translation of the same D2L book; for Vietnamese readers if the stale version is acceptable

Một cuốn sách về Học Sâu đề cập đến nhiều framework phổ biến, được sử dụng trên 300 trường Đại học từ 55 đất nước bao gồm MIT, Stanford, Harvard, và Cambridge.

predecessor MXNet-based D2L content; outdated but a historical alternative

An interactive book on deep learning. Much easy, so MXNet. Wow. [Straight Dope is growing up] ---> Much of this content has been incorporated into the new Dive into Deep Learning Book available at https://d2l.ai/.

choose for a focused accelerated NLP course, but much narrower than D2L

Machine Learning University: Accelerated Natural Language Processing Class

code companion for an older DL+CV book; valid if you want that book's examples

《深度学习与计算机视觉》配套代码