We're in the midst of an AI research explosion. Deep learning has unlocked superhuman perception to power our push toward creating self-driving vehicles, defeating human experts at a variety of difficult games including Go, and even generating essays with shockingly coherent prose. But deciphering these breakthroughs often takes a PhD in machine learning and mathematics. The updated second edition of this book describes the intuition behind these innovations without jargon or complexity. Python-proficient programmers, software engineering professionals, and computer science majors will be able to reimplement these breakthroughs on their own and reason about them with a level of sophistication that rivals some of the best developers in the field.
A very informative book that taught me a lot about the current (as of the writing) state of neural network research. Chock full of information. And math!
The book could use some deeper editing, tho'. Especially when it refers to colors in the black and white diagrams and illustrations. I didn't find all of the diagrams and illustrations useful but many were quite eye opening and were a lesson in themselves.