Features updated material on deep reinforcement learning and policy gradient methods.
The latest edition includes substantial updates to reflect the rapid advancement of the field: Deep Learning Expansion Features updated material on deep reinforcement learning and
The specific keyword is high-volume for a reason. Many students cannot afford the $70+ MIT Press hardcover. However, you must be careful. Features updated material on deep reinforcement learning and
The deep learning chapter (Ch. 17) covers only basic MLPs and backprop. No CNNs, RNNs, attention, or modern optimization (Adam barely mentioned). Published 2014 — before the deep learning explosion. Features updated material on deep reinforcement learning and
Updates to optimization techniques and regularization.