Python Machine Learning - Code Examples

Chapter 1 - Giving Computers the Ability to Learn from Data

Overview




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from IPython.display import Image

Building intelligent machines to transform data into knowledge

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The three different types of machine learning


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Image(filename='./images/01_01.png', width=500)


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Making predictions about the future with supervised learning


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Image(filename='./images/01_02.png', width=500)


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Classification for predicting class labels


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Image(filename='./images/01_03.png', width=300)


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Regression for predicting continuous outcomes


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Image(filename='./images/01_04.png', width=300)


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Solving interactive problems with reinforcement learning


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Image(filename='./images/01_05.png', width=300)


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Discovering hidden structures with unsupervised learning

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Finding subgroups with clustering


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Image(filename='./images/01_06.png', width=300)


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Dimensionality reduction for data compression


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Image(filename='./images/01_07.png', width=500)


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An introduction to the basic terminology and notations


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Image(filename='./images/01_08.png', width=500)


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A roadmap for building machine learning systems


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Image(filename='./images/01_09.png', width=700)


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Preprocessing - getting data into shape

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Training and selecting a predictive model

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Evaluating models and predicting unseen data instances

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Using Python for machine learning

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Installing Python packages

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Summary

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