Music Recommendation System Using Machine Learning

Abstract

Usually, people really need advice in deciding their choices. Whether it's the movie to watch on Friday night or there are some exciting new things available on e-business. In this distinctive situation, we tend to build a framework which will thus bring down new melodies to shoppers supported their previous history of listening. Now many companies today use the recommendation systems to their advantage such as flip kart and Amazon for the sale of products (e-commerce), ganna.com and music for streaming music, for the sale of clothes, for the films. It assists each business and customers as businesses get financial advantages by attracting customers and users pick up services. Nowadays, everyone uses recommender systems in various forms and they are getting better and better day by day because researchers are trying to cause them to higher and higher each day because of the sturdy competitiveness of the marketplace to provide higher and higher offerings and entice peoples. This project mainly focuses on music only for the music lovers to help them listen to songs they might love. This project allows customers to find new collections or the songs by making the lovey the list accessible for the tuning. Along these lines, the executive can assess which artist or collection would co-ordinate the client's inclinations towards the customers. For the music lovers, music is lifeline and music are a lovely part of the everyone's life because everything in this world can be related to frequency and vibrations. According to all the good things about the music and the high demand for recommendation systems in the market, we chose to do music recommendation system.