Dive into Deep Learning — Dive into Deep Learning 1.0.3 documentation

Dive into Deep Learning

This interactive deep learning book includes code, math, and discussions.

It supports multiple frameworks including PyTorch, NumPy/MXNet, JAX, and TensorFlow.

Currently adopted at 500 universities across 70 countries.

Dive into Deep Learning (D2L) is an interactive deep learning book that has gained significant recognition in the academic and machine learning community. Here are the key highlights:

Book Characteristics

• Implemented with multiple frameworks: PyTorch, NumPy/MXNet, JAX, and TensorFlow
• Offers an interactive learning experience combining mathematics, figures, code, text, and discussions
• Each section is an executable Jupyter notebook where users can modify code and tune hyperparameters

Academic Adoption The book has been adopted by over 500 universities across 70 countries, including prestigious institutions such as:

• Stanford University
• MIT
• Harvard University
• University of California, Berkeley
• Carnegie Mellon University
• Columbia University

Community and Learning Features

• Interactive notebooks allow instant feedback and practical deep learning experiences