Book Image

Feature Engineering Made Easy

By : Sinan Ozdemir, Divya Susarla
Book Image

Feature Engineering Made Easy

By: Sinan Ozdemir, Divya Susarla

Overview of this book

Feature engineering is the most important step in creating powerful machine learning systems. This book will take you through the entire feature-engineering journey to make your machine learning much more systematic and effective. You will start with understanding your data—often the success of your ML models depends on how you leverage different feature types, such as continuous, categorical, and more, You will learn when to include a feature, when to omit it, and why, all by understanding error analysis and the acceptability of your models. You will learn to convert a problem statement into useful new features. You will learn to deliver features driven by business needs as well as mathematical insights. You'll also learn how to use machine learning on your machines, automatically learning amazing features for your data. By the end of the book, you will become proficient in Feature Selection, Feature Learning, and Feature Optimization.
Table of Contents (14 chapters)
Title Page
Copyright and Credits
Packt Upsell
Contributors
Preface

Contributors

About the authors

Sinan Ozdemir is a data scientist, start-up founder, and educator living in the San Francisco Bay Area. He studied pure mathematics at Johns Hopkins University. He then spent several years conducting lectures on data science at Johns Hopkins University before founding his own start-up, Kylie.ai, which uses artificial intelligence to clone brand personalities and automate customer service communications.

Sinan is also the author of Principles of Data Science, available through Packt.

 

I would like to thank my parents and sister for supporting me throughout my life, and also my partner, Elizabeth Beutel. I also would like to thank my co-author, Divya Susarla, and Packt Publishing for all of their support.

 

 

 

 

 

Divya Susarla is an experienced leader in data methods, implementing and applying tactics across a range of industries and fields, such as investment management, social enterprise consulting, and wine marketing. She studied business economics and political science at the University of California, Irvine, USA.

Divya is currently focused on natural language processing and generation techniques at Kylie.ai, a start-up helping clients automate their customer support conversations.

 

I would like to thank my parents for their unwavering support and guidance, and also my partner, Neil Trivedi, for his patience and encouragement. Also, a shoutout to DSI-SF2; this book wouldn't be a reality without you all. Thanks to my co-author, Sinan Ozdemir, and to Packt Publishing for making this book possible.

About the reviewer

Michael Smith uses big data and machine learning to learn about how people behave. His experience includes IBM Watson and consulting for the US government. Michael actively publishes at and attends several prominent conferences as he engineers systems using text data and AI. He enjoys discussing technology and learning new ways to tackle problems.

 

 

 

 

 

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