Introduction
Linear regression is a statistical method that estimates the relationship between a dependent variable and one or more independent variables. It can be used to test hypotheses, make predictions, or explore the data. Linear regression assumes that the relationship between the variables is linear, meaning that it can be represented by a straight line. There are different types of linear regression, such as simple, multiple, and logistic, depending on the number and nature of the independent variables.
Contents
The Linear Model: Hypothesis and Loss
Regularization
Minimum Norm Interpolation
Bayesian View of Linear Regression