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dc.contributor.advisorRahman, Tanvir
dc.contributor.authorSadman, Syed Hassan
dc.contributor.authorRahat, Hasib Al
dc.contributor.authorHamim, Atikur Rahman
dc.contributor.authorAl Kafi, Sultan Gias Uddin
dc.contributor.authorKhan, Nasik Ali
dc.date.accessioned2021-09-09T11:30:55Z
dc.date.available2021-09-09T11:30:55Z
dc.date.copyright2021
dc.date.issued2021-06
dc.identifier.otherID 17101238
dc.identifier.otherID 17101017
dc.identifier.otherID 17101089
dc.identifier.otherID 17301203
dc.identifier.otherID 20301459
dc.identifier.urihttp://hdl.handle.net/10361/14991
dc.descriptionThis thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2021.en_US
dc.descriptionCataloged from PDF version of thesis.
dc.descriptionIncludes bibliographical references (page 34).
dc.description.abstractThe stock market plays an important role in the growth of industries by supplying funding. Thousands of Bangladeshis use the stock market as a means of employment. The stock markets in Bangladesh have been declining lately, impacting millions of individuals. What if stock markets could allow investors to know which stock is more reliable or less dependable. We will be using the Linear Regression algorithms along with the K-Nearest Neighbors algorithm, the Support Vector Machine (SVM), Lasso Regression and Multi-Linear Regression to predict the stocks.en_US
dc.description.statementofresponsibilitySyed Hassan Sadman
dc.description.statementofresponsibilityHasib Al Rahat
dc.description.statementofresponsibilityAtikur Rahman Hamim
dc.description.statementofresponsibilityA.R.M. Emtiaj Al Kafi
dc.description.statementofresponsibilityNasik Ali Khan
dc.format.extent34 pages
dc.language.isoenen_US
dc.publisherBrac Universityen_US
dc.rightsBrac 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.
dc.subjectData Miningen_US
dc.subjectMachine Learningen_US
dc.subjectStock Marketen_US
dc.subjectPredictionen_US
dc.subjectLinear Regression Analysisen_US
dc.subjectK-Nearest Neighbouren_US
dc.subjectSupport Vector Machineen_US
dc.subjectLassoen_US
dc.subjectAnalysisen_US
dc.subject.lcshMarket share--Bangladesh
dc.titleData analysis on the Bangladesh share market using Machine-Learningen_US
dc.typeThesisen_US
dc.contributor.departmentDepartment of Computer Science and Engineering, Brac University
dc.description.degreeB. Computer Science


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