Math for Deep Learning provides the essential math you need to understand deep learning discussions, explore more complex implementations, and better use the deep learning toolkits.With Math for Deep Learning, you'll learn the essential mathematics used by and as a background for deep learning. You’ll work through Python examples to learn key deep learning related topics in probability, statistics, linear algebra, differential calculus, and matrix calculus as well as how to implement data flow in a neural network, backpropagation, and gradient descent. You’ll also use Python to work through the mathematics that underlies those algorithms and even build a fully-functional neural network.In addition you’ll find coverage of gradient descent including variations commonly used by the deep learning community: SGD, Adam, RMSprop, and Adagrad/Adadelta.
✔ Author(s): Ronald T. Kneusel
✔ Title: Math for Deep Learning: What You Need to Know to Understand Neural Networks
✔ Rating : 4 out of 5 base on (45 reviews)
✔ ISBN-10: 1718501900
✔ ISBN-13: 9781718501904
✔ Language: English
✔ Format ebook: PDF, EPUB, Kindle, Audio, HTML and MOBI
✔ Device compatibles: Android, iOS, PC and Amazon Kindle
Readers' opinions about Math for Deep Learning by Ronald T. Kneusel
Beata Shepard
The world created in this book was unlike anything I've ever encountered. The author's imagination knows no bounds, and I was completely mesmerized by the fantastical setting.
Virginia Savage
I'm already planning to reread this book. It's one of those stories that you can revisit again and again, discovering new layers of meaning each time.
Tasha Cobbett
The themes of resilience and hope resonated deeply with me. This book taught me valuable life lessons that I'll carry with me for years to come.
