Real-World Machine Learning

Chapter 3. Modeling and prediction

This chapter covers

• Discovering relationships in data through ML modeling
• Using models for prediction and inference
• Building classification models
• Building regression models

The previous chapter covered guidelines and principles of data collection, preprocessing, and visualization. The next step in the machine-learning workflow is to use that data to begin exploring and uncovering the relationships that exist between the input features and the target. In machine learning, this process is done by building statistical models based on the data. This chapter covers the basics required to understand ML modeling and to start building your own models. In contrast to most machine-learning textbooks, we spend ...