About this book
Grokking Deep Learning was written to help give you a foundation in deep learning so that you can master a major deep learning framework. It begins by focusing on the basics of neural networks and then switches its focus to provide an in-depth look at advanced layers and architectures.
I’ve intentionally written this book with what I believe is the lowest barrier to entry possible. No knowledge of linear algebra, calculus, convex optimization, or even machine learning is assumed. Everything from those subjects that’s necessary to understand deep learning will be explained as we go. If you’ve passed high school mathematics and hacked around in Python, you’re ready for this book.
This book has 16 chapters: