I have read many books on deep learning, and many of them talk about theory where it is beyond the reach of the average reader who doesn't have a strong math background of a MS in the sciences, or is about programming them in some language or library, but they very rarely break things down and explain them the way this book does. While the book may lack mathematical rigour and deep explanations and proofs, it makes a very good attempt at trying to simplify concepts to make them intuitive for readers who are trying to get into the field and don't come from a strong mathematical background. On the cover, the book claims to cover a breadth of topics but it seems to be focused on the main classes of neural networks (FNNs, CNNs, RNNs) and gives brief introductions to the other topics. I had struggled with many concepts like backpropagation in recurrent and convolutional nets, but this book explained it very well and very simply. If you’re looking to get into the field of deep learning, I highly recommend this reading this book.