The use of matrix factorizations in recommendation systems is widely. If you want to quickly and easily develop a solution to provide excellent recommendations to your clients, then you will get a good and simple starting point from this video:
The above video contains following content :
02:55 Why reservations
04:10 Create slots
08:31 Delete slots
09:00 Train model
12:47 Running Pipeline
Extra supporting credit:
Check out the two Google articles if you're new to matrix factorization and BigQuery ML.
- Recommendations with implicit feedback https://cloud.google.com/bigquery-ml/docs/bigqueryml-mf-implicit-tutorial
- Recommendations with explicit feedback
The data used in the video demonstration and the Google BigQuery ML examples are identical. No need to reinvent the wheel in this case.