Bests & Worsts Reviews from Amazon

The book was frankly a disappointment. It was unclear who the intended audience was. If it were the people who wanted to find out academic background behind Deep Learning, then this would be too superficial for them. In some cases, it’s not even clear who and how someone would benefit from the presented material. (For instance, whom was the Linear Algebra chapter written for? It’s woefully impossible to understand if you don’t already know linear algebra. And if you already know it, it’s unnecessary. And if you sort of know it and wanted to brush up, what linear algebra they present in the chapter is not enough to go through the math in the book. So…) If it’s for the people who want to get started with deep learning, it’s completely off topic, since it presents the mathematical nitty-gritty of the deep learning algorithms without mentioning any specifics of how to train a convo-net for example. The amount of information on convolutional networks and LSTMs is worse than on any number of blogs on deep learning or Wikipedia. If you’re really interested in Math behind Deep Learning out of curiousity (perhaps you’re a mathematician who wants to know what this deep learning thing is all about) perhaps this is a book for you. Otherwise, do yourself a favor and watch/read Andrej Karpathy’s Stanford class.