Filename: register_sas_classification_model.py
Level: Beginner
Registers a classification model in SAS Model Manager that was created from a SAS algorithm with SWAT.
Filename: register_sas_regression_model.py
Level: Beginner
Registers a regression model in SAS Model Manager that was created from a SAS algorithm with SWAT.
Filename: register_sas_dlpy_model.py
Level: Beginner
Creates a SAS deep learning model using dlpy and registers the model in SAS Model Manager.
Filename: register_scikit_classification_model.py
Level: Beginner
Registers a classification model in SAS Model Manager that was created from a Python algorithm with scikit-learn.
Filename: register_scikit_regression_model.py
Level: Beginner
Registers a regression model in SAS Model Manager that was created from a Python algorithm with scikit-learn.
Filename: full_lifecycle.py
Level: Beginner
Demonstrates how sasctl can be used throughout the lifecycle of a model by:
- training multiple Python models with scikit-learn
- registering them to SAS Model Manager
- publishing them to SAS's real-time scoring engine (MAS)
- executing the models in real-time
- creating a report to track model performance over time
Filename: register_custom_model.py
Level: Intermediate
Registers a model in SAS Model Manager by explicitly providing the files and model details.
Filename: FleetManagement.ipynb
Level: Intermediate
Trains multiple tree-based models using scikit-learn and registers them in SAS Model Manager. Also uses the pzmm module of sasctl to generate and include model fit statistics and ROC/Lift charts.
Filename: data_science_pilot.ipynb
Level: Intermediate
Uses the swat package to perform automated modeling on a dataset. Registers the results along with a custom XGBoost model to SAS Model Manager using sasctl.
Filename: direct_REST_calls.py
Level: Advanced
Demonstrates using sasctl to make REST calls over HTTP(S) directly to the SAS microservices.
Use if you need to customize behavior or use functionality not yet exposed through higher-level sasctl functions.