Training and deployment framework for machine learning based recommendation system

Abstract

Disclosed herein is a training and deployment framework for a machine learning based recommendation system. In one aspect, a computer-implement method is provided for synthesizing training and testing data and using the training and testing data to generate a machine learning model. The computer-implement method includes deriving product ratings for products, the product ratings being stored in a user product score table in association with identifiers for users and the products, sampling the user product score table to generate a training and testing data set, training, using the training data set, machine learning models for a task of predicting product ratings, evaluating, using the testing data set, performance of the machine learning models, selecting one of the machine learning models for production use in predicting product ratings based on the evaluating, and predicting, using the selected machine learning model, new product ratings for the products.