Generalized Additive Models - A journey from linear regression to GAMs

A presentation for data scientists. We start by discussing the need for simple and interpretable models. Then we start with ordinary linear squares regression and work our way to generalized additive models (GAMs). PDF slides: https://tommyodland.com/files/presentations/linreg_to_gam.pdf Implementation: https://github.com/tommyod/generalized-additive-models Table of contents: 00:01:51 - The need for simple models 00:09:10 - Linear regression 00:14:32 - Ridge regression 00:24:56 - Ridge with a link function 00:42:37 - Generalized Additive Models 01:00:26 - Summary Keywords: linear regression, knn, tree, feature engineering, Excel, SQL, machine learning, ML, generalized linear model, generalized additive model, loss function, matrix, calculus, normal equations, optimization, modeling, ridge, link function, inverse link function, logistic, softmax, Gauss-Newton algorithm, Newton's method, Taylor expansion, gradient, Hessian, spline basis, B-spline, second order difference matrix, powerlifting, multiplicative effect, log link, tensor spline, additive, interactions, interaction terms, likelihood, gamma, poisson, logistic,