diff --git a/README.md b/README.md
index 68c0690..43bd75a 100644
--- a/README.md
+++ b/README.md
@@ -72,5 +72,4 @@ using NotebookManagementTools
 generate(joinpath("docs", "src", "notebooks", "02_models"))
 ```
 
-but change "02_models" to the tutorial you are testing. If you are adding a brand new
-tutorial, *do commit* the generated markdown, but for updates this is discouraged.
+but change "02_models" to the tutorial you are testing. 
diff --git a/docs/src/notebooks/MLJTutorial/03_pipelines/Project.toml b/docs/src/notebooks/MLJTutorial/03_pipelines/Project.toml
index 0aec77b..4d6edff 100644
--- a/docs/src/notebooks/MLJTutorial/03_pipelines/Project.toml
+++ b/docs/src/notebooks/MLJTutorial/03_pipelines/Project.toml
@@ -10,7 +10,7 @@ MLJMultivariateStatsInterface = "1b6a4a23-ba22-4f51-9698-8599985d3728"
 [compat]
 CSV = "0.10.16"
 DataFrames = "1.8.2"
-EvoTrees = "0.18"
+EvoTrees = "0.19"
 MLJ = "0.23.3"
 MLJLinearModels = "0.10.2"
 MLJMultivariateStatsInterface = "0.5.4"
\ No newline at end of file
diff --git a/docs/src/notebooks/MLJTutorial/04_tuning/Project.toml b/docs/src/notebooks/MLJTutorial/04_tuning/Project.toml
index 6ee66fd..00fc4d9 100644
--- a/docs/src/notebooks/MLJTutorial/04_tuning/Project.toml
+++ b/docs/src/notebooks/MLJTutorial/04_tuning/Project.toml
@@ -12,7 +12,7 @@ Plots = "91a5bcdd-55d7-5caf-9e0b-520d859cae80"
 CSV = "0.10.16"
 DataFrames = "1.8.2"
 Distributions = "0.25.130"
-EvoTrees = "0.18"
+EvoTrees = "0.19"
 MLJ = "0.23.3"
 MLJLinearModels = "0.10.2"
 Plots = "1.41.6"
diff --git a/docs/src/notebooks/MLJTutorial/04_tuning/notebook.jl b/docs/src/notebooks/MLJTutorial/04_tuning/notebook.jl
index 0bc7eaa..f546592 100644
--- a/docs/src/notebooks/MLJTutorial/04_tuning/notebook.jl
+++ b/docs/src/notebooks/MLJTutorial/04_tuning/notebook.jl
@@ -237,11 +237,13 @@ tree_booster = EvoTreeRegressor(nrounds = 70)
 model = ContinuousEncoder |> tree_booster
 
 # (a) Construct a bounded range `r1` for the `evo_tree_booster`
-# parameter `max_depth`, varying between 1 and 12.
+# parameter `max_depth`, varying between 4 and 14.
 
 # (b) For the `colsample` parameter of the `EvoTreeRegressor`, define the range
 
-r2 = range(model, :(evo_tree_regressor.colsample), lower=0.5, upper=1.0)
+r2 = range(model, :(evo_tree_regressor.nbins), values = [32, 64, 128])
+
+# (a)
 
 # Optimize `model` over these the parameter ranges `r1` and `r2` using a random search
 # with uniform priors (the default). Use `Holdout()` resampling, and implement your search
diff --git a/docs/src/notebooks/MLJTutorial/99_solution_to_exercises/Project.toml b/docs/src/notebooks/MLJTutorial/99_solution_to_exercises/Project.toml
index c7b8b05..1cca7c0 100644
--- a/docs/src/notebooks/MLJTutorial/99_solution_to_exercises/Project.toml
+++ b/docs/src/notebooks/MLJTutorial/99_solution_to_exercises/Project.toml
@@ -17,7 +17,7 @@ CSV = "0.10.16"
 DataFrames = "1.8.2"
 Distributions = "0.25.130"
 Downloads = "1.7.0"
-EvoTrees = "0.18"
+EvoTrees = "0.19"
 MLJ = "0.23.3"
 MLJClusteringInterface = "0.1.13"
 MLJDecisionTreeInterface = "0.5.0"
diff --git a/docs/src/notebooks/MLJTutorial/99_solution_to_exercises/notebook.jl b/docs/src/notebooks/MLJTutorial/99_solution_to_exercises/notebook.jl
index 5dfff05..c089477 100644
--- a/docs/src/notebooks/MLJTutorial/99_solution_to_exercises/notebook.jl
+++ b/docs/src/notebooks/MLJTutorial/99_solution_to_exercises/notebook.jl
@@ -1,4 +1,4 @@
-# # Solutions to Exercises 
+# # Solutions to Exercises
 
 using MLJ, Downloads, CSV, DataFrames, Plots
 nothing #hide
@@ -330,11 +330,11 @@ EvoTreeRegressor = @load EvoTreeRegressor
 tree_booster = EvoTreeRegressor(nrounds = 70)
 model = ContinuousEncoder |> tree_booster
 
-r2 = range(model, :(evo_tree_regressor.colsample), lower=0.5, upper=1.0)
+r2 = range(model, :(evo_tree_regressor.nbins), values = [32, 64, 128])
 
 # (a)
 
-r1 = range(model, :(evo_tree_regressor.max_depth), lower=1, upper=12)
+r1 = range(model, :(evo_tree_regressor.max_depth), lower=4, upper=14)
 
 # (b)