fixes to exercises

Author: SkafteNicki

s2_organisation_and_version_control/cli.md

@@ -209,13 +209,19 @@ for doing this, and of other excellent frameworks for creating command line inte
 
     ```bash
     python iris_classifier.py train svm --kernel 'linear'
-    python iris_classifier.py train knn -k 5
+    python iris_classifier.py train knn --n-neighbors 5
     ```
 
     e.g the `train` command now has two subcommands for training different machine learning models (in this case SVM
     and KNN) which each takes arguments that are unique to that model. Relevant
     [documentation](https://typer.tiangolo.com/tutorial/subcommands/).
 
+    !!! warning "`_` vs `-`"
+
+        When using typer do not that variables with `_` in the name
+        will be converted to `-` in the CLI. Meaning that if you have a variable `n_neighbors` in your code, you should use
+        `--n-neighbors` in the CLI.
+
     ??? success
 
         ```python linenums="1" title="iris_classifier.py"

s2_organisation_and_version_control/exercise_files/typer_exercise_solution3.py

@@ -38,9 +38,9 @@ def svm(kernel: str = "linear", output_file: Annotated[str, typer.Option("--outp
 
 
 @train_app.command()
-def knn(k: int = 5, output_file: Annotated[str, typer.Option("--output", "-o")] = "model.ckpt") -> None:
+def knn(n_neighbors: int = 5, output_file: Annotated[str, typer.Option("--output", "-o")] = "model.ckpt") -> None:
     """Train a KNN model."""
-    model = KNeighborsClassifier(n_neighbors=k)
+    model = KNeighborsClassifier(n_neighbors=n_neighbors)
     model.fit(x_train, y_train)
 
     with open(output_file, "wb") as f:

s3_reproducibility/config_files.md

@@ -80,7 +80,7 @@ or using `hydra` for loading the configuration
 ```python
 import hydra
 
-@hydra.main(config_name="basic.yaml")
+@hydra.main(config_name="config.yaml")
 def main(cfg):
     print(cfg.hyperparameters.batch_size, cfg.hyperparameters.learning_rate)
 

s5_continuous_integration/cml.md

@@ -342,6 +342,10 @@ repository.
                 types: staged_model
             ```
 
+            Do note that the `repository_dispatch` event will only trigger a workflow run if the workflow file exists
+            on the default branch. Therefore, if you are testing this on a branch, you need to push the workflow file
+            to the default branch.
+
     8. Next, we need to implement the steps in our workflow that do something when a model is staged. The payload that
         is sent to the webhook contains information about the model that was staged. Implement a workflow that: