Python Machine Learning - Code Examples

Chapter 1 - Giving Computers the Ability to Learn from Data

Overview

Building intelligent machines to transform data into knowledge
The three different types of machine learning
A roadmap for building machine learning systems
Using Python for machine learning
Installing Python packages
Summary



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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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from IPython.display import YouTubeVideo
YouTubeVideo("Pi9NpxAvYSs")









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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)









    



---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
<ipython-input-1-17272bec90e1> in <module>()
----> 1 Image(filename='./images/01_03.png', width=300)

NameError: name 'Image' is not defined

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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Applications



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Atari game
Go
Self Driving Car
Object Recognition
Scene Understanding
Medical diagnostics
Music Generation
Art Generation (Mario levels)
Story Writing
Speech recognition (personal assistants, chat bots)
Face recognition

Competitions



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Kagel cancer detection 
Youtube 8m video
multi-class pixelwise segmentation
imageNet (Large Scale Visual Recognition Challenge)

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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