Machine Learning_ Make Your Own Recommender System (Machine Learning From Scratch Book 3)_Oliver Theobald [Theobald, Oliver].pdf

Machine Learning for Beginners: Make Your Own Recommender System   Machine Learning for Beginners Series   Published by Scatterplot Press       Oliver Theobald     First Edition Copyright © 2018 by Oliver Theobald Published by Scatterplot Press 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 [email protected] for feedback, media contact, omissions or errors regarding this book. TABLE OF CONTENTS   FOREWORD DATASETS USED IN THIS BOOK INTRODUCTION THE ANATOMY SETTING UP A SANDBOX ENVIRONMENT WORKING WITH DATA DATA REDUCTION COLLABORATIVE FILTERING PART 1 COLLABORATIVE FILTERING PART 2 CONTENT-BASED FILTERING EVALUATION PRIVACY & ETHICS THE FUTURE OF RECOMMENDER SYSTEMS FURTHER RESOURCES Find Us On:   Skillshare www.skillshare.com/user/machinelearning_beginners   Teachable http://scatterplotpress.teachable.com/   YouTube Scatterplot Media   Instagram machinelearning_beginners FOREWORD From relevant friend suggestions on Facebook to product recommendations on Amazon, there’s no missing the presence of recommender systems. Take a look at what you’ve recently viewed and consumed online because many of your online activities, including finding this book, probably originated from algorithm-backed recommendations. These data-driven systems are eroding the dominance of traditional search engines while aiding the discoverability of niche and esoteric items. As a breakaway branch of machine learning, it’s more important than ever to understand how these models work, and in this book, we go a step further by coding three basic recommender systems. This book is designed for beginners with