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    •   BracU IR
    • School of Data and Sciences (SDS)
    • Department of Computer Science and Engineering (CSE)
    • Thesis & Report, BSc (Computer Science and Engineering)
    • View Item
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    Data analysis on the Bangladesh share market using Machine-Learning

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    17101238, 17101017, 17101089, 17301203, 20301459_CSE.pdf (2.253Mb)
    Date
    2021-06
    Publisher
    Brac University
    Author
    Sadman, Syed Hassan
    Rahat, Hasib Al
    Hamim, Atikur Rahman
    Al Kafi, Sultan Gias Uddin
    Khan, Nasik Ali
    Metadata
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    URI
    http://hdl.handle.net/10361/14991
    Abstract
    The 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.
    Keywords
    Data Mining; Machine Learning; Stock Market; Prediction; Linear Regression Analysis; K-Nearest Neighbour; Support Vector Machine; Lasso; Analysis
     
    LC Subject Headings
    Market share--Bangladesh
     
    Description
    This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2021.
     
    Cataloged from PDF version of thesis.
     
    Includes bibliographical references (page 34).
    Department
    Department of Computer Science and Engineering, Brac University
    Collections
    • Thesis & Report, BSc (Computer Science and Engineering)

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