updating release notes

docs/core_classes/transforms/features_to_model.md

@@ -80,7 +80,7 @@ to_model.transform(target_column=None, description="Wine 2D Projection", train_a
 For custom models we recommend the following steps:
 
 !!! warning inline end "Experimental"
-    The SageWorks Custom Models are currently in experimental mode so have fun but expect issues. Requires `sageworks >= 0.8.59`. Feel free to submit issues to [SageWorks Github](https://github.com/SuperCowPowers/sageworks)
+    The SageWorks Custom Models are currently in experimental mode so have fun but expect issues. Requires `sageworks >= 0.8.60`. Feel free to submit issues to [SageWorks Github](https://github.com/SuperCowPowers/sageworks)
 
 - Copy the example custom model script into your own directory
     - See: [Custom Model Script](https://github.com/SuperCowPowers/sageworks/tree/main/src/sageworks/model_scripts/custom_script_example)

docs/release_notes/0_8_58.md

@@ -11,7 +11,7 @@ The SageWorks framework continues to flex to support different real world use ca
 ## General
 This release is an incremental release as part of the road map for `v.0.9.0`. Please see the full details of the planned changes here: [v0.9.0 Roadmap](../road_maps/0_9_0.md). 
 
-### Caching Refatoring
+### Caching Refactoring
 We've created a new set of Cached Classes:
 
 - CachedDataSource

docs/release_notes/0_8_60.md

@@ -0,0 +1,39 @@
+# Release 0.8.60
+
+!!!tip inline end "Need Help?"
+    The SuperCowPowers team is happy to give any assistance needed when setting up AWS and SageWorks. So please contact us at [[email protected]](mailto:[email protected]) or on chat us up on [Discord](https://discord.gg/WHAJuz8sw8) 
+
+The SageWorks framework continues to flex to support different real world use cases when operating a set of production machine learning pipelines.
+
+**Note:** These release notes cover the changes from `0.8.58` to `0.8.60`
+
+
+## General
+This release is an incremental release as part of the road map for `v.0.9.0`. Please see the full details of the planned changes here: [v0.9.0 Roadmap](../road_maps/0_9_0.md). 
+
+### Custom Models
+We've now exposed additional functionality and API around adding your own custom models. The new custom model support is documented on the [Features to Models](../core_classes/transforms/features_to_model.md) page.  
+
+
+## API Changes
+None
+
+## Notes
+Custom models introduce models that don't have model metrics or inference runs, so you'll see a lot of log messages complaining about not finding metrics or inference results, please just ignore those, we'll put in additional logic to address those cases.
+
+
+## Specific Code Changes
+
+<a href="https://github.com/supercowpowers/sageworks/compare/v0.8.58...v0.8.60" target="_blank">Code Diff v0.8.58 --> v0.8.60</a> 
+
+Who doesn't like looking at code! Also +3 points for getting down this far! Here's a cow joke as a reward:
+
+> ***What do you call a nonsense meeting?
+      .... Moo-larkey***
+
+## Questions?
+<img align="right" src="../../images/scp.png" width="180">
+
+The SuperCowPowers team is happy to answer any questions you may have about AWS and SageWorks. Please contact us at [[email protected]](mailto:[email protected]) or on chat us up on [Discord](https://discord.gg/WHAJuz8sw8) 
+
+

mkdocs.yml

@@ -84,6 +84,7 @@ nav:
     - 0.9.0:  road_maps/0_9_0.md
     - 0.9.5:  road_maps/0_9_5.md
   - Release Notes: 
+    - 0.8.60:  release_notes/0_8_60.md
     - 0.8.58:  release_notes/0_8_58.md
     - 0.8.55:  release_notes/0_8_55.md
     - 0.8.50:  release_notes/0_8_50.md

src/sageworks/core/transforms/features_to_model/features_to_model.py

@@ -18,6 +18,7 @@ class FeaturesToModel(Transform):
 
     Common Usage:
         ```python
+        from sageworks.core.transforms.features_to_model.features_to_model import FeaturesToModel
         to_model = FeaturesToModel(feature_uuid, model_uuid, model_type=ModelType)
         to_model.set_output_tags(["abalone", "public", "whatever"])
         to_model.transform(target_column="class_number_of_rings",
@@ -285,7 +286,6 @@ def create_and_register_model(self):
 if __name__ == "__main__":
     """Exercise the FeaturesToModel Class"""
 
-    """
     # Regression Model
     input_uuid = "abalone_features"
     output_uuid = "abalone-regression"
@@ -299,18 +299,14 @@ def create_and_register_model(self):
     to_model = FeaturesToModel(input_uuid, output_uuid, ModelType.CLASSIFIER)
     to_model.set_output_tags(["wine", "public"])
     to_model.transform(target_column="wine_class", description="Wine Classification")
-    """
 
     # Quantile Regression Model (Abalone)
-    """
     input_uuid = "abalone_features"
     output_uuid = "abalone-quantile-reg"
     to_model = FeaturesToModel(input_uuid, output_uuid, ModelType.QUANTILE_REGRESSOR)
     to_model.set_output_tags(["abalone", "quantiles"])
     to_model.transform(target_column="class_number_of_rings", description="Abalone Quantile Regression")
-    """
 
-    """
     # Scikit-Learn Kmeans Clustering Model
     input_uuid = "wine_features"
     output_uuid = "wine-clusters"
@@ -349,18 +345,15 @@ def create_and_register_model(self):
     )
     to_model.set_output_tags(["wine", "2d-projection"])
     to_model.transform(target_column=None, description="Wine 2D Projection", train_all_data=True)
-    """
 
     # Custom Script Models
     scripts_root = Path(__file__).resolve().parents[3] / "model_scripts"
-    """
     my_custom_script = scripts_root / "custom_script_example" / "custom_model_script.py"
     input_uuid = "wine_features"
     output_uuid = "wine-custom"
     to_model = FeaturesToModel(input_uuid, output_uuid, model_type=ModelType.CLASSIFIER, custom_script=my_custom_script)
     to_model.set_output_tags(["wine", "custom"])
     to_model.transform(target_column="wine_class", description="Wine Custom Classification")
-    """
 
     # Temp Molecular Descriptors Model
     my_script = scripts_root / "custom_models" / "chem_info" / "rdkit_mordred_features.py"