As machine learning is increasingly leveraged to find patterns, conduct analysis, and make decisions - sometimes without final input from humans who may be impacted by these findings - it is crucial to invest in bringing more stakeholders into the fold. This book of Python projects in machine learning tries to do just that: to equip the developers of today and tomorrow with tools they can use to better understand, evaluate, and shape machine learning to help ensure that it is serving us all.
This book will set you up with a Python programming environment if you don't have one already, then provide you with a conceptual understanding of machine learning in the chapter "An Introduction to Machine Learning." What follows next are three Python machine learning projects. They will help you create a machine learning classifier, build a neural network to recognize handwritten digits, and give you a background in deep reinforcement learning through building a bot for Atari.
This open book is licensed under a Creative Commons License (CC BY-NC-SA). You can download Python Machine Learning Projects ebook for free in PDF format (2.1 MB).
Table of Contents
Setting Up a Python Programming Environment
An Introduction to Machine Learning
How To Build a Machine Learning Classifier in Python with Scikit-learn
How To Build a Neural Network to Recognize Handwritten Digits with TensorFlow
Bias-Variance for Deep Reinforcement Learning: How To Build a Bot for Atari with OpenAI Gym
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