Description
Dive into Deep Learning is an interactive deep learning book with code, math and discussions, written by Aston Zhang, Zack C. Lipton, Mu Li and Alex J. Smola with additional chapter authors. It is implemented in PyTorch, NumPy/MXNet, JAX and TensorFlow, and each section is an executable Jupyter notebook, so readers can change the code and tune hyperparameters to see the effect at once. Later additions cover reinforcement learning, Gaussian processes, hyperparameter optimization and transformers for vision and large-scale pretraining. The site says the book has been adopted at 500 universities from 70 countries. A fit for developers who want theory and runnable code side by side.
