Math for Deep Learning

Ronald T. Kneusel

Acheter 39,42 €
+ 39 points
Langue:
Ebook en anglais
ISBN:
9781718501911
Date de parution:
22-11-21
Nombre de pages:
344
Editeur:
No Starch Press
Format:
Ebook
Format Détaillé:
EPUB
Protection digitale:
/

Description

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.