Update EXGBoost version in notebook (#279)

notebooks/cv_gradient_boosting_tree.livemd

@@ -3,7 +3,7 @@
 ```elixir
 Mix.install([
   {:scholar, "~> 0.2.0"},
-  {:exgboost, "~> 0.3"},
+  {:exgboost, "~> 0.5"},
   {:req, "~> 0.3.9"},
   {:kino_vega_lite, "~> 0.1.9"},
   {:kino, "~> 0.10.0"},
@@ -22,6 +22,13 @@ require Explorer.DataFrame, as: DF
 require Explorer.Series, as: S
 ```
 
+And let's configure `EXLA` as our default backend (where our tensors are stored) and compiler (which compiles Scholar code) across the notebook and all branched sections:
+
+```elixir
+Nx.global_default_backend(EXLA.Backend)
+Nx.Defn.global_default_options(compiler: EXLA)
+```
+
 We are going to work with [Medical Cost Personal Datasets](https://www.kaggle.com/datasets/mirichoi0218/insurance) to predict medical charges that were applied to each person from the dataset. Let's download it:
 
 ```elixir