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    • Αποθετήριο Ανοικτού Πανεπιστημίου Κύπρου (Repository of the Open University of Cyprus)
    • Μεταπτυχιακές διατριβές / Master Τhesis
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    • Αποθετήριο Ανοικτού Πανεπιστημίου Κύπρου (Repository of the Open University of Cyprus)
    • Μεταπτυχιακές διατριβές / Master Τhesis
    • Πληροφοριακά και Επικοινωνιακά Συστήματα (ΕΛΛ) / Information and Communication Systems (in Greek)
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    Machine learning algorithms comparison

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    ΠΕΣ-2017-00274.pdf (608.6Kb)
    Date
    2017
    Author
    Papamanolioudakis, Nikolaos
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    Abstract
    The current thesis is a first approach on Machine Learning from the writer with very fundamental knowledge on this subject. On the other hand the writer having a great experience on Databases considered the transition natural (albeit not a smooth one). Like history, Machine Learning looks on the past (in this case existing data) and attempts to predict future situations (based on new data) and likewise to fictional character Harry Seldon and his psychohistory on Isaac Asimov's best novel "Last Foundation" you cannot predict the notions and ideas of one person but you can predict how the masses will move even in the far future if the number of persons that are part of the under examination mass is sufficiently big. Generally speaking machine learning is the process which gives to machines/computers the possibility to learn without the intervention or explicit guidance of the developer.
    URI
    http://hdl.handle.net/11128/3217
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    • Πληροφοριακά και Επικοινωνιακά Συστήματα (ΕΛΛ) / Information and Communication Systems (in Greek)

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    Open University of Cyprus

    PO Box 12794,

    2252, Latsia

    Cyprus

    Tel.: +357 22 411600

    Fax.: +357 22 411601

    • Help
    • Contact Us
    • Open University of Cyprus
    • OUC Library
    • Policies
    • Accessibility and Data Protection

    Find us on:

    • FacebookFacebook
    • EU Flag
    • Republic of Cyprus
    • Structural Funds
    • e University
    • Open University of Cyprus

    The eUniversity Project is co-founded by the European Regional Development Fund and National Funds in the Programmatic Period 2007-2013