Introduction to Statistical and Machine Learning Methods for Data Science

Chapter 4: Supervised Models – Machine Learning Approach

Chapter Overview

In this chapter you will learn about supervised machine learning models. Chapter 3 covered supervised statistical models such as linear regression, logistic regression, and decision trees. Chapter 4 covers machine learning models including random forests, gradient boosting models, and artificial neural networks.

The main goals of this chapter are:

• Identify situations that could benefit from using machine learning supervised models.
• Identify some advantages in terms of performance, flexibility, and accuracy, and some disadvantages like the lack of interpretability.
• Describe diverse types of machine learning supervised models and the circumstances under which they might ...