In this chapter, we studied two very popular machine learning algorithms, namely linear regression and logistic regression. We saw how linear regression can be used to predict continuous values such as sales counts, estimating the price of products, and so on. We also ran a sample case study using the linear regression approach to predict the prices of houses. We later learned about logistic regression and ran a sample using a popular heart disease dataset used for studying machine learning.
In the next chapter, we will learn two more supervised learning algorithms that are used heavily in classification. The first algorithm that we will study is Naive Bayes and then we will learn about the support vector machine algorithm.
