Math for Deep Learning
What You Need to Know to Understand Neural Networks
1 of 1 copy available
1 of 1 copy available
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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Creators
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Publisher
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Release date
November 23, 2021 -
Formats
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OverDrive Read
- ISBN: 9781718501911
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EPUB ebook
- ISBN: 9781718501911
- File size: 26716 KB
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Languages
- English
Formats
- OverDrive Read
- EPUB ebook
subjects
Languages
- English
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