Supervised Learning
In this third part of the book, our focus will be on the the following chapters:
In ?sec-basics-supervised-learning we will get to understand the basics of supervised learning from a theoretical and practical standpoint.
In 10 Linear Regression we will dive into linear regression from a theoretical and practical standpoint.
In 11 K-Nearest Neighbour Regression we will understand the k-Nearest Neighbours (kNN) regression algorithm as a classic method for nonlinear data.
In 12 Classification Using Logistic Model we will dive into classification models.