Summary

In this chapter, you learned about the concept of feature engineering and why it is an important part of the whole machine learning process. Additionally, you learned why it is required to create features and train machine learning models.

You explored various feature engineering techniques such as feature extraction and how they can be used to convert text-based data into features. Feature transformation techniques useful in dealing with categorical and continuous variables were introduced, and examples of how to convert them into features were presented. You also explored feature scaling techniques that are useful for normalizing features to help prevent some features from unduly biasing the trained model.

Finally, you were introduced to techniques for selecting the right features to optimize the model performance for the label being predicted via feature selection techniques. The skills learned in this chapter will help you to implement scalable and performant feature...