Statistical Methods for Machine Learning_ Discover How to Transform Data into Knowledge with Python_Jason Brownlee.pdf

Statistical Methods for Machine Learning Discover how to Transform Data into Knowledge with Python Jason Brownlee i Disclaimer The information contained within this eBook is strictly for educational purposes. If you wish to apply ideas contained in this eBook, you are taking full responsibility for your actions. The author has made every eort to ensure the accuracy of the information within this book was correct at time of publication. The author does not assume and hereby disclaims any liability to any party for any loss, damage, or disruption caused by errors or omissions, whether such errors or omissions result from accident, negligence, or any other cause. No part of this eBook may be reproduced or transmitted in any form or by any means, electronic or mechanical, recording or by any information storage and retrieval system, without written permission from the author. Acknowledgements Special thanks to my copy editor Sarah Martin and my technical editors Arun Koshy and Andrei Cheremskoy. Copyright Statistical Methods for Machine Learning ©Copyright 2019 Jason Brownlee. All Rights Reserved. Edition: v1.4 Contents Copyright i Contents ii Preface iii I Introduction II Statistics 1 Introduction to Statistics 1.1 Statistics is Required Prerequisite 1.2 Why Learn Statistics? 1.3 What is Statistics? 1.4 Further Reading 1.5 Summary 2 Statistics vs Machine Learning 2.1 Machine Learning 2.2 Predictive Modeling 2.3 Statistical Learning 2.4 Two Cultures 2.5 Further Reading 2.6 Summary 3 Examples of Statistics in Machine Learning 3.1 Overview 3.2 Problem Framing 3.3 Data Understanding 3.4 Data Cleaning 3.5 Data Selection 3.6 Data Preparation 3.7 Model Evaluation 3.8 Model Conguration 3.9 Model Selection ii CONTENTS iii 3.10 Model Presentation 3.11 Model Predictions 3.12 Summary III Foundation 4 Gaussian and Summary Stats 4.1 Tutorial Overview 4.2 Gaussian Distribution 4.3 Sample vs Population 4.4 Test Dataset 4.5 Central Tendency 4.6 Variance 4.7 Describing a Gaussian