This series of posts is intended to summarize the contents or note memorable things in Mathematics for ML book which I’ve got some insights from the contents. The book is『MATHEMATICS for MACHINE LEARNING, Marc Peter Deisenroth, A. Aldo Faisal and Cheng Soon Ong, Cambridge University Press. https://mml-book.com』. This post is about 2nd Chapter of …
From below I’ve quoted some paragraphs from page 59~page 70 directly in the ISLR book. Recall the Advertising data from Chapter 2. The figure below displays sales for a particular product as a function of advertising budgets for TV, radio, and newspaper media. Suppose that in our role as statistical consultants we are asked …
Read moreISLR chapter 03. Linear Regression_3.1 Simple Linear Regression
2.1 What Is Statistical Learning? X : input variables; predictors; independent variables Y : output variables; response; dependent variable Suppose that we observe a quantitative response Y and p different predictors, . We assume that there is some relationship between Y and 《Very general form》 2.1.1 Why Estimate f ? ① Prediction We can …
A Brief History of Statistical Learning Though the term statistical learning is fairly new, many of the concepts that underlie the field were developed long ago. At the beginning of the nineteenth century, Legendre and Gauss published papers on the method of least squares, which implemented the first successfully applied to problems in astronomy. Linear …