Bias, Variance, and Regularization in Linear Regression: Lasso, Ridge, and Elastic Net -- Differences and uses

Regression is an incredibly popular and common machine learning technique. Often the starting point in learning machine learning, linear regression is an intuitive algorithm for easy-to-understand problems. It can generally be used whenever you're trying to predict a continuous variable (a variable that can take any value in some numeric range), linear regressions and its relatives are often strong options, and are almost always the best place to start. This blog assumes a functional knowledge of ordinary least squares (OLS) linear regression. You can read more about OLS linear regression here, here, or here.