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

Chapter 1. Introduction to Feature Engineering

In recent years, engineers and executives have been attempting to implement machine learning (ML) and artificial intelligence (AI) to solve problems that, for the most part, have been solved using fairly manual methodologies. A great example would have to be advancements in natural language processing (NLP) and more specifically in natural language generation and understanding. Even more specifically, we point to AI systems that are able to read in raw text from a user (perhaps a disgruntled user of the latest smartphone) and can articulately and accurately respond with the prose of a human and the speed of a machine. In this chapter, we will be introducing topics of feature engineering, such as: 

  • Motivating examples of why feature engineering matters
  • Basic understanding of machine learning, including performance, evaluation
  • A detailed list of the chapters included in this book