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Programming Machine Learning
book

Programming Machine Learning

by Paolo Perrotta
March 2020
Beginner to intermediate content levelBeginner to intermediate
342 pages
8h 38m
English
Pragmatic Bookshelf
Content preview from Programming Machine Learning

Understanding Activation Functions

By now, you’re familiar with activation functions—those cyan boxes in between a neural network’s layers shown in the diagram.

images/taming/network_plan.png

All our activation functions so far have been sigmoids, except in the output layer, where we used the softmax function.

The sigmoid has been with us for a long time. I originally introduced it to squash the output of a perceptron so that it ranged from 0 to 1. Later on, I introduced the softmax to rescale a neural network’s outputs so that they added up to 1. By rescaling the outputs, we could interpret them as probabilities, as in: “we have a 30% chance that this picture contains a platypus.” ...

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Publisher Resources

ISBN: 9781680507706Errata Page