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. 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.
Price: 37.55 USD
Location: East Hanover, New Jersey
End Time: 2024-11-29T02:59:46.000Z
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EAN: 9781718501904
UPC: 9781718501904
ISBN: 9781718501904
MPN: N/A
Number of Pages: 344 Pages
Publication Name: Math for Deep Learning : What You Need to Know to Understand Neural Networks
Language: English
Publisher: No Starch Press, Incorporated
Publication Year: 2021
Subject: Neural Networks, General, Calculus
Item Height: 0.9 in
Type: Textbook
Item Weight: 23.2 Oz
Item Length: 9.1 in
Subject Area: Mathematics, Computers, Science
Author: Ronald T. Kneusel
Item Width: 7 in
Format: Trade Paperback
