Table of Contents

 

Copyright

Brief Table of Contents

Table of Contents

Preface

Acknowledgments

About this Book

About the Cover Illustration

1. Preparing and gathering data and knowledge

Chapter 1. Philosophies of data science

1.1. Data science and this book

1.2. Awareness is valuable

1.3. Developer vs. data scientist

1.4. Do I need to be a software developer?

1.5. Do I need to know statistics?

1.6. Priorities: knowledge first, technology second, opinions third

1.7. Best practices

1.7.1. Documentation

1.7.2. Code repositories and versioning

1.7.3. Code organization

1.7.4. Ask questions

1.7.5. Stay close to the data

1.8. Reading this book: how I discuss concepts

Summary

Chapter 2. Setting goals by asking good questions

2.1. Listening to the customer

2.1.1. Resolving wishes and pragmatism

2.1.2. The customer is probably not a data scientist

2.1.3. Asking specific questions to uncover fact, not opinions

2.1.4. Suggesting deliverables: guess and check

2.1.5. Iterate your ideas based on knowledge, not wishes

2.2. Ask good questions—of the data

2.2.1. Good questions are concrete in their assumptions

2.2.2. Good answers: measurable success without too much cost