From e798dac4114816e4e31d32c36c61a222ab291fda Mon Sep 17 00:00:00 2001 From: hadley Date: Fri, 22 Jul 2016 08:57:07 -0500 Subject: [PATCH] Model book rec tweaks --- model.Rmd | 16 +++++++++------- 1 file changed, 9 insertions(+), 7 deletions(-) diff --git a/model.Rmd b/model.Rmd index 27e1f57..b9ac9cb 100644 --- a/model.Rmd +++ b/model.Rmd @@ -65,18 +65,20 @@ The modelling chapters are even more opinionated than the rest of the book. I ap * *Statistical Modeling: A Fresh Approach* by Danny Kaplan, . This book provides a gentle introduction to modelling, where you build your intuition, - mathematical tools, and R skills in parallel. + 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, +* *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. + 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). * *Applied Predictive Modeling* by Max Kuhn and Kjell Johnson, . This book is a companion to the __caret__ package, and provides practical tools for dealing with real-life predictive modelling challenges. - -