updates shap book box

christophM · Aug 21, 2023 · 310329e · 310329e
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diff --git a/manuscript/05.9-agnostic-shapley.Rmd b/manuscript/05.9-agnostic-shapley.Rmd
@@ -14,7 +14,7 @@ Shapley values -- a method from coalitional game theory -- tells us how to fairl
 
 ```{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.
+[I got you covered](https://leanpub.com/shap).
 ```
 
 ### General Idea

diff --git a/manuscript/05.9b-agnostic-shap.Rmd b/manuscript/05.9b-agnostic-shap.Rmd
@@ -12,7 +12,7 @@ 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.
+[I got you covered](https://leanpub.com/shap).
 ```
 
 There are two reasons why SHAP got its own chapter and is not a subchapter of [Shapley values](#shapley).
@@ -21,11 +21,6 @@ And they proposed TreeSHAP, an efficient estimation approach for tree-based mode
 Second, SHAP comes with many global interpretation methods based on aggregations of Shapley values.
 This chapter explains both the new estimation approaches and the global interpretation methods.
 
-```{block2, type = "rmdnote", echo = is.html, eval=is.html}
-Just looking for the correct interpretation of SHAP lots?
-Save yourself time and get the [SHAP plots cheat sheet](https://christophmolnar.gumroad.com/l/shap-plots-for-tabular-data).
-```
-
 
 I recommend reading the chapters on [Shapley values](#shapley) and [local models (LIME)](#lime) first.
 
@@ -424,6 +419,11 @@ For the receivers of a SHAP explanation, it is a disadvantage: they cannot be su
 ### Software
 
 The authors implemented SHAP in the [shap](https://github.com/slundberg/shap) Python package.
+
+```{block2, type = "rmdnote", echo = is.html, eval=FALSE}
+The book [Interpreting Machine Learning Models with SHAP](https://leanpub.com/shap) covers the application of SHAP with the `shap` package in depth.
+```
+
 This implementation works for tree-based models in the [scikit-learn](https://scikit-learn.org/stable/) machine learning library for Python.
 The shap package was also used for the examples in this chapter.
 SHAP is integrated into the tree boosting frameworks [xgboost](https://github.com/dmlc/xgboost/tree/master/python-package) and [LightGBM](https://github.com/microsoft/LightGBM).