diff --git a/docs/src/basic-example.jl b/docs/src/basic-example.jl
index d3352a2..ccb681f 100644
--- a/docs/src/basic-example.jl
+++ b/docs/src/basic-example.jl
@@ -33,6 +33,8 @@ md"""
 # Basic Example
 
 This page shows a basic example for using SIRUS.jl on a dataset via the Machine Learning Julia (MLJ.jl) interface.
+For more details on what SIRUS is and how it works, see the
+[Advanced Example](/dev/binary-classification).
 """
 
 # ╔═╡ 3e9f7866-edaa-460a-81d4-abf76ab066dc
@@ -171,6 +173,7 @@ For this measure, a score of 0.5 means that our model is as good (or bad, actual
 """
 
 # ╔═╡ b8c6c9e0-679e-41d5-80c0-ffd65e652489
+# ╠═╡ show_logs = false
 evaluate(model, X, y; resampling, measure=auc)
 
 # ╔═╡ Cell order:
diff --git a/docs/src/index.md b/docs/src/index.md
index 0c5377b..fe41855 100644
--- a/docs/src/index.md
+++ b/docs/src/index.md
@@ -22,7 +22,8 @@ These rules fully explain the predictions while remaining easy to interpret.
 
 ## Where to Start?
 
-- [Binary Classification Example](/dev/binary-classification)
+- [Basic Example](/dev/basic-example)
+- [Advanced Example](/dev/binary-classification)
 
 ## Acknowledgements