In this directory, notebooks are provided to demonstrate how to tune and optimize hyperparameters of recommender algorithms with the utility functions (reco_utils) provided in the repository.
| Notebook | Description |
|---|---|
| hypertune_spark_deep_dive | Step by step tutorials on how to fine tune hyperparameters for Spark based recommender model (illustrated by Spark ALS) with Spark native construct and hyperopt package. |
| hypertune_aml_wide_and_deep_quickstart | Quickstart tutorial on utilizing Azure Machine Learning service for hyperparameter tuning of wide-and-deep model. |