In this directory, notebooks are provided to demonstrate the use of different algorithms such as Alternating Least Squares (ALS) and Smart Adaptive Recommendations (SAR). The notebooks show how to establish an end-to-end recommendation pipeline that consists of data preparation, model building, and model evaluation by using the utility functions (reco_utils) available in the repo.
| Notebook | Description |
|---|---|
| als_pyspark_movielens | Utilizing the ALS algorithm to predict movie ratings in a PySpark environment. |
| sar_python_cpu_movielens | Utilizing the Smart Adaptive Recommendations (SAR) algorithm to predict movie ratings in a Python+CPU environment. |