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: tommyodland.co...
Implementation: github.com/tom...
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,

[@farooqpetersaidi7784]

Nice Tutorial ❤, keep it up

[@webelod4999]

Thanks!

[@ekstrapolatoraproksymujacy412]

audio level very low