It’s now customary for B2C ecommerce sites to provide consumers with tailored recommendations for purchases. By using previous transaction and browsing data, combined with an expansive pool of product feedback (for example, ratings and reviews), developers can build applications leveraging the power of built-in machine learning with Oracle HeatWave AutoML. That enables them to train a model and generate inferences on the data stored in an object store as well as in a MySQL database.
In this solution, we’ll build a movie recommendation application (MovieHub) using Heatwave and Oracle APEX, Oracle’s low-code platform. The HeatWave AutoML recommender system delivers movie suggestions to users while providing admins with powerful analytics dashboards on movie consumption and user behavior.