A Machine Learning Based Implementation of Product and Service Recommendation Models

Most of the internet based companies are now relying on the capabilities of recommendation models to increase their product sales. By applying efficient recommendation models businesses can track their customer preferences and effectively recommend products to users thereby increasing their sales. This paper describes the prototype implementation of two recommendations models using machine learning algorithms. The first prototype system is a banking service recommendation system and the second one is a movie recommendation system. These prototype implementations are evidence of how effectively machine learning algorithms can be applied for designing recommendation models.