Abstract

Regression is a fundamental machine learning algorithm which is often used for classification and prediction problems. It uses a linear or nonlinear combination of variables or function of variables to predict a value of an output variable.

Content:

1. What is Linear Regression
2. Supervised Learning
3. Theory and Usage of Linear Regression
4. Model Choice
5. Cost Function and Equation Derivation
6. Advantages and Disadvantages
7. Polynomial Regression