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, <http://www-bcf.usc.edu/~gareth/ISL/> (available online for free).
+-   *An Introduction to Statistical Learning* by Gareth James, Daniela Witten, Trevor Hastie, and Robert Tibshirani, <https://www.statlearning.com> (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, <https://web.stanford.edu/~hastie/Papers/ESLII.pdf> (also available online for free).