Chapter 2. Classification and Regression Using Supervised Learning
In this chapter, we are going to learn about classification and regression of data using supervised learning techniques. By the end of this chapter, you will know about these topics:
- What is the difference between supervised and unsupervised learning?
- What is classification?
- How to preprocess data using various methods
- What is label encoding?
- How to build a logistic regression classifier
- What is Naïve Bayes classifier?
- What is a confusion matrix?
- What are Support Vector Machines and how to build a classifier based on that?
- What is linear and polynomial regression?
- How to build a linear regressor for single variable and multivariable data
- How to estimate housing prices using Support Vector Regressor
