Chapter 5. Improving Model Accuracy
Note
Learning Objectives
By the end of this chapter, you will be able to:
Explain the concept of regularization
Explain the procedures of different regularization techniques
Apply L1 and L2 regularization to improve accuracy
Apply dropout regularization to improve accuracy
Describe grid search and random search hyperparameter optimizers in scikit-learn
Use hyperparameter tuning in scikit-learn to improve model accuracy
Note
In this chapter, we will learn about the concept of regularization and different regularization techniques. We will then use regularization to improve accuracy. We will also learn how to use hyperparameter tuning to improve model accuracy.
