Linear regression from scratch: OLS, the design matrix trick, and QR decomposition
Linear regression is one of the simplest models in machine learning. It is usually one of the first algorithms encountered in most conventional machine learning courses, with its final form deceptively straightforward: take some input variables, multiply them by a set of coefficients, add an intercept, and obtain a prediction.