Deep Learning with R

Chapter 4. Fundamentals of machine learning

This chapter covers

• Forms of machine learning beyond classification and regression
• Formal evaluation procedures for machine-learning models
• Preparing data for deep learning
• Feature engineering
• Tackling overfitting
• The universal workflow for approaching machine-learning problems

After the three practical examples in chapter 3, you should be starting to feel familiar with how to approach classification and regression problems using neural networks, and you’ve witnessed the central problem of machine learning: overfitting. This chapter will formalize some of your new intuition into a solid conceptual framework for attacking and solving deep-learning problems. In section 4.5, we’ll consolidate all of ...