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 2. Feature Understanding – What's in My Dataset?

Finally! We can start to jump into some real data, some real code, and some real results. Specifically, we will be diving deeper into the following ideas:

  • Structured versus unstructured data
  • Quantitative versus qualitative data
  • The four levels of data
  • Exploratory data analysis and data visualizations
  • Descriptive statistics

Each of these topics will give us a better sense of the data given to us, what is present within the dataset, what is not present within the dataset, and some basic notions on how to proceed from there.

If you're familiar with, Principles of Data Science, much of this echoes Chapter 2, Types of Data of that book. That being said, in this chapter, we will specifically look at our data less from a holistic standpoint, and more from a machine-learning standpoint.