mention new book project

christophM · Mar 2, 2023 · fef82bb · fef82bb
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diff --git a/manuscript/05.9-agnostic-shapley.Rmd b/manuscript/05.9-agnostic-shapley.Rmd
@@ -13,8 +13,8 @@ A prediction can be explained by assuming that each feature value of the instanc
 Shapley values -- a method from coalitional game theory -- tells us how to fairly distribute the "payout" among the features.
 
 ```{block2, type = "rmdnote", echo = is.html, eval=FALSE}
-Interested in an in-depth, hands-on course on SHAP and Shapley values?
-Head over to [the Shapley course page](https://leanpub.com/c/shapley-xai) and get notified once the course is available.
+Looking for an in-depth, hands-on book on SHAP and Shapley values?
+Head over to [Leanpub](https://leanpub.com/shap) and get notified once the book is available.
 ```
 
 ### General Idea

diff --git a/manuscript/05.9b-agnostic-shap.Rmd b/manuscript/05.9b-agnostic-shap.Rmd
@@ -10,6 +10,11 @@ set.seed(42)
 SHAP (SHapley Additive exPlanations) by Lundberg and Lee (2017)[^lundberg2017] is a method to explain individual predictions.
 SHAP is based on the game theoretically optimal [Shapley values](#shapley).
 
+```{block2, type = "rmdnote", echo = is.html, eval=FALSE}
+Looking for an in-depth, hands-on book on SHAP and Shapley values?
+Head over to [Leanpub](https://leanpub.com/shap) and get notified once the book is available.
+```
+
 There are two reasons why SHAP got its own chapter and is not a subchapter of [Shapley values](#shapley).
 First, the SHAP authors proposed KernelSHAP, an alternative, kernel-based estimation approach for Shapley values inspired by [local surrogate models](#lime).
 And they proposed TreeSHAP, an efficient estimation approach for tree-based models.