Real-World Machine Learning

Chapter 5. Basic feature engineering

This chapter covers

• Understanding the importance of feature engineering for your machine-learning project
• Using basic feature-engineering processes, including processing dates and times and simple texts
• Selecting optimal features and reducing the statistical and computational complexity of the model
• Using feature engineering at model-building and prediction time

The first four chapters have shown you how to fit, evaluate, and optimize a supervised machine-learning algorithm, given a set of input features and a target of interest. But where do those input features come from? How do you go about defining and calculating features? And how do practitioners know whether they’re using the right set of features ...