Feature Engineering Made Easy: Identify unique features from your dataset in order to build powerful machine learning systems

by Sinan Özdemir, Divya Susarla

A perfect guide to speed up the predicting power of machine learning algorithms 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 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 also learn to convert a problem statement into useful new features. This book will guide you in delivering features driven by business needs as well as mathematical insights, and you'll see how to use machine learning for your data. By the end of the book, you will have become proficient in feature selection, feature learning, and feature pptimization. If you are a data science professional or a machine learning engineer looking to strengthen your predictive analytics model, then this book is a perfect guide for you. Some basic understanding of machine learning concepts and Python scripting would be enough to get started with this book.

Genres: Programming

316 pages, Paperback

Published January 22, 2018

Reviews

[Andrey · Rating 3 out of 5]

More like "Guide to preprocessing data using scikit-learn". Good code examples, not so good algorithm explanations