Covers everything from Bayesian decision theory to CNNs.
Is there a (e.g., 3rd edition) you are looking at? Neural Networks, Machine Learning, and Image Pr...
Requires a solid grasp of linear algebra and probability. Pros and Cons The Good: Clear explanations of complex optimization problems. Logical progression from simple classifiers to deep models. Includes helpful end-of-chapter problems for self-study. The Bad: Covers everything from Bayesian decision theory to CNNs