Deep Learning

Written by some of the most important figures in AI research, this book is indispensable for anyone trying to understand what AI is all about. Despite written by true experts, it is a surprisingly understandable and lucid guide to the subject - accessible to anyone with rudimentary understanding of machine learning at the high school level.

I truly believe that this is the book that brought my generation of AI experts into the fold. Despite having studied AI and ML, this book took me by the hand and grounded me in the fundamentals. I love the fact that it covers everything from mathematical basics to industry-level techniques.

Written by the OGs of deep learning, it's an absolute must-read for anyone serious about the field. Highly recommend for students and engineers alike.

Deep learning burst on the scene in 2012 with the success of the AlexNet model in the ImageNet competition. The first comprehensive deep learning text was this one, released in 2016.

It’s almost a necessity for deep learning practitioners, but it is not for beginners. Think of it as a graduate-level text. After eight years, some portions read as slightly dated, but the essentials have not changed.

This is a very technical, truly academic book. I’d recommend reading it 4th or 5th if you felt that prior books did not have sufficient rigour. While this book is academic, it has been lauded by many for its clarity. This is a great book to really think about fundamentals and see what sorts of things can go wrong—even in applied settings.