Arif, HossainShihab, Ibne FarabiOishi, Maliha Moonwara2018-12-032018-12-0320182018ID 14201002ID 14301011http://hdl.handle.net/10361/10951Cataloged from PDF version of thesis.Includes bibliographical references (pages 45-47).This thesis is submitted in partial fulfilment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2018.A restaurant business is a very prospective and profitable business nowadays. However, ensuring quality food, good stuff, inner-environment etc. is a big concern and most importantly before facing all these, the trickiest part is to choose a perfect place where a restaurant business will flourish. Without doing a perfect research on this area, setting up a restaurant may lead to an immediate downfall. Not only for choosing a preferred restaurant location, people are now hiring professionals to do ground check and here the data scientists are coming into play as a bigshot. This research is focused on suggesting a suitable place for setting up a restaurant business based on the existing data from Yelp where 75 features have been extracted for analysis. Several machine learning algorithms (Support Vector Machine, Decision Tree, Logistic Regression and Decision Tree with presort) have been used and juxtaposed to nurture out the suitable one. As yelp’s review is authentic and it is maintained regularly, we have considered the rating of a business as the point of suggestion. We have also looked at the comparative analysis of this algorithm and searched for an algorithm which gives us the best result.47 pagesenBRAC University theses 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.Vector MachineDecision TreeLogistic regressionRestaurantGeographical locationMachine learningData miningThesis