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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

Where Perceptrons Fail

What’s not to love about perceptrons? They’re simple, and they can be assembled into larger structures like machine learning construction bricks. However, that simplicity comes with a distressing limitation: perceptrons work well on some datasets, and fail badly on others. More specifically, perceptrons are a good fit for linearly separable data. Let’s see what “linearly separable” means, and why it matters.

Linearly Separable Data

Take a look at this two-dimensional dataset:

images/perceptron/linearly_separable_2_clusters.png

The two classes in the data—green triangles and blue squares—are neatly arranged into distinct clusters. You could even separate them with a line, ...

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Publisher Resources

ISBN: 9781680507706Errata Page