• Shivang Agarwal
• Shivang Kanwar
• Simranjeet Singh Dua
• Piyush Bhardwaj

Recommendation system assumes essential job in Internet world and is utilized in numerous applications. It has made the accumulation of numerous applications, created global village and development for various data. Today there is a major wide range of methodologies and algorithms of data filtering and recommendation. In this paper we portray the proposal framework related research and after that presents different strategies and methodologies utilized by the recommender system User based approach, Item-based approach, Hybrid suggestion approaches, Association rule learning, Clustering and related research in the recommender system. At last we will demonstrate the fundamental difficulties and issues recommender systems go over.

Recommendation, Collaborative filtering, Model based, Memory based, Content based, Hybrid, Clustering, Apriori.

"Diverse Approaches for Machine Learning Based Recommendation System ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 4, page no.151-155, April-2019, Available :http://www.jetir.org/papers/JETIR1904P27.pdf

"Diverse Approaches for Machine Learning Based Recommendation System ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 4, page no. pp151-155, April-2019, Available at : http://www.jetir.org/papers/JETIR1904P27.pdf