This work explores probabilistic models of supervised learning problems and addresses the key statistical and computational questions. Chapters survey research

presents a unified and in-depth development of neural network learning algorithms and neural network expert systems

This book covers both classical and modern models in deep learning. The primary focus is on the theory and algorithms of deep learning. The theory and algorithm

Using the tools of complexity theory, Stephen Judd develops a formal description of associative learning in connectionist networks. He rigorously exposes the co

This book is for anyone who wants to understand what neural network[s] are. It's for anyone who wants to make and use their own. And it's for anyone who wants t