Machine Learning For Absolute
Beginners
Oliver Theobald
First Edition
Copyright © 2017 by Oliver Theobald
All rights reserved. No part of this publication may be reproduced,
distributed, or transmitted in any form or by any means, including
photocopying, recording, or other electronic or mechanical
methods, without the prior written permission of the publisher,
except in the case of brief quotations embodied in critical reviews
and certain other non-commercial uses permitted by copyright law.
Please contact the author at oliver.******@ for
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Table of Contents
INTRODUCTION
FROM DATA SCIENCE, TO AI, TO MACHINE LEARNING
SELF-LEARNING
TOOLS
MACHINE LEARNING TECHNIQUES
INTRODUCTION
MACHINE LEARNING IN ACTION
REGRESSION ANALYSIS
CLUSTERING ANALYSIS
DIMENSIONALITY REDUCTION
SUPPORT VECTOR MACHINES
ARTIFICIAL NEURAL NETWORKS
BIAS & VARIANCE
DECISION TREES
ASSOCIATION ANALYSIS
RECOMMENDER SYSTEMS
ALGORITHM SELECTION
DEVELOPMENT ENVIRONMENT
BUILDING A MODEL IN PYTHON
WHERE TO GO NEXT
CAREER & STUDY OPTIONS
FURTHER RESOURCES
DOWNLOADING DATASETS
1
INTRODUCTION
It’s a Friday night at home, and you’ve just placed your smartphone down on
the kitchen table after ordering a pizza. Within seconds of putting down the
phone, you receive a message from your friend who wants to hang out at your
house tonight. While you don’t mind your friend joining you, this
arrangement is less than ideal.
First, your friend doesn’t have a car. If your friend is to come over, you will
need to drive over to his house to collect him. This usually wouldn’t be a
problem, as you could wait for the pizza to arrive, eat a few slices, and then
leave to collect your friend from his house. But tonight, that would mean
missing the start of an important sports game televised live on TV. Once the
match begins, you won’t be leaving the living room for a
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