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Browsing by Subject "Machine learning"

Browsing by Subject "Machine learning"

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  • Bitcoin estimation and prediction through neural network and machine learning 
    Hanna, Marianne G. (Notre Dame University-Louaize, 2021)
    Bitcoin is the most popular purely digital cryptocurrency nowadays. It started in 2009 as a peer to peer payment system, decentralized, pseudo-anonymous and secure system of money. The main objective of this study is to estimate and predict the weekly close bitcoin price by including other variables like commodities, indexes and demand / supply variables through different kind of machine learning and deep learning such as multiple regression, time series ARIMA model, artificial neural network, combination of multiple regression and ARIMA model, and finally combination of multiple regression, ...
  • Cyber risk loss modelling in cyber insurance 
    Al Ghandour, Maria Gerges (Notre Dame University-Louaize, 2021)
    In today's world, protecting information has become one of the most difficult tasks. Cyber security events and data breaches continue to be expensive events that affect people and businesses all around the world. A breach occurs when sensitive information is accessed. Moreover, cyber threats are constantly evolving in order to take advantage of online behavior and trends, especially when teleworking has become a necessity due to the global invasion and prevalence of the Coronavirus disease 2019 during the past two years. Therefore, the necessity for cyber insurance, which covers the liability ...
  • Escaping the echo chamber in movies recommender system 
    El Haddad, Anthony (Notre Dame University-Louaize, 2022-07)
    With the considerable rise of Internet users and the massive and diverse web searches, an excess of data has become available online. A recommendation model, also known as an engine, handles this massive amount of data available to find patterns that reflect user behaviors. Recommendation models have been implemented in several industries, and the most popular implementation is in the entertainment industry, specifically video streaming and on-demand platforms. There are several types of recommendation systems. In this paper, we have proposed a way to escape the loop created by the recommendation ...
  • Technology and the current covid-19 
    Simonian, Roy (Notre Dame University-Louaize, 2022)
    The world is witnessing nowadays a virus that spreads in a very fast manner and it has infected a large number of people. Countries rushed to find ways to stop this virus from spreading and to minimize the risks of getting infected. One of these ways was to integrate technology in people’s daily routine to help in containing the virus. In fact, although several countries took a lot of legal measurements and law enforcement to prevent the spread of the virus, such as wearing facial masks, social distancing, using sanitizers and other forms of hygiene supplements, there were always the need to ...
  • Using transfer learning for malware detection 
    Rammouz, Veronica (Notre Dame University-Louaize, 2021)
    The internet has made room for lots of unwanted activity to propagate through computers. In response, many methods were established to detect a certain computer executable as malicious. However, there were still loopholes for hackers within traditional systems. Some methods use machine learning others use deep learning. There are some drawbacks to each method, such as reverse analysis and restricted simulation on different execution paths, as well as long execution time. Some methods cannot generalize well and cannot scale to large amounts of data. Moreover, anti-viruses, using signature-based ...