Chapter 3: Data Preparation and Transformation
You have probably heard that data scientists spend most of their time working on data preparation-related activities. It is now time to explain why that happens and which types of activities we are talking about.
In this chapter, you will learn how to deal with categorical and numerical features, as well as applying different techniques to transform your data, such as one-hot encoding, binary encoders, ordinal encoding, binning, and text transformations. You will also learn how to handle missing values and outliers in your data, which are two important tasks you can implement to build good machine learning models.
In this chapter, we will cover the following topics:
- Identifying types of features ...