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Math for Deep Learning
book

Math for Deep Learning

by Ronald T. Kneusel
October 2021
Intermediate to advanced
344 pages
8h 51m
English
No Starch Press
Content preview from Math for Deep Learning

7DIFFERENTIAL CALCULUS

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The discovery of “the calculus” by Sir Issac Newton, and separately by Gottfried Wilhelm Leibniz, was one of the greatest achievements in the history of mathematics. Calculus is typically split into two main parts: differential and integral. Differential calculus talks about rates of change and their relationships, embodied in the notion of the derivative. Integral calculus is concerned with things like the area under a curve.

We don’t need integral calculus for deep learning, but we’ll use differential calculus often. For example, we use differential calculus to train neural networks; we adjust the weights of a neural network ...

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Publisher Resources

ISBN: 9781098129101