Math for Deep Learning

Name: Math for Deep Learning
Brand: Random House Publishing
SKU: 9781718501904
Price: 754 CZK
Availability: InStock

Autor: Ronald T. Kneusel

Jazyk:

Vazba: Brožovaná

Vydavatel: Random House Publishing

Dostupnost: Skladem u dodavatele

Odesíláme za 3-6 dnů

754 Kč

Math for Deep Learning provides the essential math you need to understand deep learning discussions,...

Informace o knize

Autor

Ronald T. Kneusel

Jazyk

Angličtina

Vazba

Kniha - Brožovaná

Vydáno

2021

Stránek

344

EAN

9781718501904

ISBN

1718501900

Enbook ID

36537261

Vydavatel

Random House Publishing

Hmotnost

636

Rozměry

177 x 232 x 24

Kompletní popis

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.

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Math for Deep Learning

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Kompletní popis

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