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    A machine learning approach to predict movie box-office success 

    Quader, Nahid; Gani, MD. Osman (BRAC University, 2017)
    Making a prediction of society’s reaction to a new product in the sense of popularity and adaption rate has become an emerging field of data analysis. The motion picture industry is a multi-billion dollar business. And ...
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    Using deep learning algorithms to detect violent activities 

    Ammar, S.M. Rojin; Anjum, Md. Tanvir Rounak; Islam, Md. Touhidul Islam (BRAC University, 2019-05)
    It is of extensive importance to develop a technique for automatic surveillance video analysis to recognize the presence of violence. In this work, to identify violent videos, we put forward a deep neural network. For ...
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    Forecasting stock market prices using advanced tools of machine learning 

    Anwar, Md. Tawhid; Rahman, Saidur (BRAC University, 2019-04)
    Stock market, a very unpredictable sector of nance, involves a large number of investors,buyers and sellers. Stock market prediction is the act of attempting to see the long run price of an organization stock or di erent ...
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    Learning a deep neural network for predicting phishing website 

    Das, Robat; Hossain, Md. Mukhter; Islam, Shariful; Siddiki, Abujarr (Brac University, 2019-05)
    In recent years, we have seen a huge paradigm shift in business because of the fast development of the Web. For this reason, consumers change their tendency from customary shopping to the electronic business. In the time ...
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    Forecasting market movement in Dhaka Stock Exchange: LSTM vs. ARIMA 

    Chakraborty, Pranjal (Brac University, 2019-04)
    This paper creates and examines the performance of LSTM models against ARIMA models, using Dhaka Stock Exchange data from beginning of 2000 to the beginning of 2019. An algorithm has been designed to simultaneously train ...
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    A supervised machine learning approach to predict vulnerability to drug addiction 

    Faisal, Fahim; Shahriar, Arif; Mahmud, Sohan Uddin; Shuvo, Rakibul Alam (Brac University, 2019-08)
    There are signi cant amount of di erences between an addicted and non-addicted person on their social and familial behavior. In our thesis we tried to nd out the characteristics of a person related to his social and ...

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    AuthorAmmar, S.M. Rojin (1)Anjum, Md. Tanvir Rounak (1)Anwar, Md. Tawhid (1)Chakraborty, Pranjal (1)Das, Robat (1)Faisal, Fahim (1)Gani, MD. Osman (1)Hossain, Md. Mukhter (1)Islam, Md. Touhidul Islam (1)Islam, Shariful (1)... View MoreSubject
    Machine learning (6)
    Neural network (6)
    Machine learning. (3)Neural networks (Computer science) (2)Random forest (2)Artificial intelligence (1)Autoregressive integrated moving average (1)Capital market (1)DarkNet-19 (1)Data mining (1)... View MoreDate Issued2019 (5)2017 (1)Has File(s)Yes (6)

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