Recommendation and Rating System using Machine Learning

This paper deals with a recommendation and rating system using machine learning algorithms like linear regression, random forest regression and support vector model. Recommendation and rating systems are subdivision of structures that filter information. These structures normally are dedicated software program components, which contribute to a bigger software program machine, but also can be standalone equipment. Our recommendation and rating system’s main aim is to give suggestions for items that the user demands which can be favorable in a collaborative approach using machine learning models. The recommendations are associated with specific choice-making mechanisms, distinctive techniques, which includes, what commodities to shop for, what shows to watch, or what holiday places to look for. This collaborative technique should be able to compute the relationship among distinct clients and depending upon their ratings and prescribe items to others who’ve comparable tastes and also finally allowing users to discover more.