Arif, HossainOrnab, Ashique MohaiminChowdhury, SakiaToa, Seevieta Biswas2018-02-202018-02-20201712/26/2017ID 13201080ID 14101252ID 14101003http://hdl.handle.net/10361/9535Cataloged from PDF version of thesis report.Includes bibliographical references (pages 60-61).This thesis report is submitted in partial fulfilment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2017.The purpose of this research is to study the different techniques that can be approached in order to build a recommendation system. Here, we have analyzed the different approaches between two different collaborative filtering algorithms in perspective of a food diet recommendation system. A food recommendation system that will help people to choose their daily meal just the way we select movies to watch from suggestions in Netflix or add a friend in Facebook when the suggestion pops up in our home page. Sometimes people get bored of having the same food items on regular basis hence in order to help them get rid out of this monotonous lifestyle, we have proposed a diet recommendation system. In this paper, we first give you some basic information about what recommendation system is, and then we talk about the two collaborative algorithms and finally tell you what kind of approaches we have used to build a diet recommendation system.61 pagesenBRAC University thesis reports are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission.Cosine similaritiesMatrix factorizationALSRecommendation systemThesis