From 7cce8df10887e80036c7efb740076a7e577226de Mon Sep 17 00:00:00 2001 From: Jakob Krigovsky Date: Wed, 13 Apr 2022 16:20:00 +0200 Subject: [PATCH] Update link to An Introduction to Statistical Learning (#1005) --- extra/model/model-building.Rmd | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/extra/model/model-building.Rmd b/extra/model/model-building.Rmd index a786ebe..8baaea3 100644 --- a/extra/model/model-building.Rmd +++ b/extra/model/model-building.Rmd @@ -487,7 +487,7 @@ Modelling really deserves a book on its own, so I'd highly recommend that you re This book provides a gentle introduction to modelling, where you build your intuition, mathematical tools, and R skills in parallel. The book replaces a traditional "introduction to statistics" course, providing a curriculum that is up-to-date and relevant to data science. -- *An Introduction to Statistical Learning* by Gareth James, Daniela Witten, Trevor Hastie, and Robert Tibshirani, (available online for free). +- *An Introduction to Statistical Learning* by Gareth James, Daniela Witten, Trevor Hastie, and Robert Tibshirani, (available online for free). This book presents a family of modern modelling techniques collectively known as statistical learning. For an even deeper understanding of the math behind the models, read the classic *Elements of Statistical Learning* by Trevor Hastie, Robert Tibshirani, and Jerome Friedman, (also available online for free).