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Machine Learning with Python for Everyone
book

Machine Learning with Python for Everyone

by Mark Fenner
August 2019
Beginner to intermediate content levelBeginner to intermediate
353 pages
18h 48m
English
Addison-Wesley Professional
Content preview from Machine Learning with Python for Everyone

3. Predicting Categories: Getting Started with Classification

In [1]:

# setup
from mlwpy import *
%matplotlib inline

3.1 Classification Tasks

Now that we’ve laid a bit of groundwork, let’s turn our attention to the main attraction: building and evaluating learning systems. We’ll start with classification and we need some data to play with. If that weren’t enough, we need to establish some evaluation criteria for success. All of these are just ahead.

Let me squeeze in a few quick notes on terminology. If there are only two target classes for output, we can call a learning task binary classification. You can think about {Yes, No}, {Red, Black}, or {True, False} targets. Very often, binary problems are described mathematically using {-1, +1} or ...

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Publisher Resources

ISBN: 9780134845708