Description

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.

Math For Deep Learning: What You Need to Know to Understand Neural Networks

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RRP: £47.99 You save £4.80 (10%)
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Paperback / softback by Ron Kneusel

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Description:

With Math for Deep Learning, you'll learn the essential mathematics used by and as a background for deep learning. You'll... Read more

    Publisher: No Starch Press,US
    Publication Date: 07/12/2021
    ISBN13: 9781718501904, 978-1718501904
    ISBN10: 1718501900

    Number of Pages: 344

    Non Fiction , Computing

    Description

    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.

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