dc.contributor.advisor | Τοκατλίδου, Αθηνά | |
dc.contributor.author | Papamanolioudakis, Nikolaos | |
dc.contributor.other | Παπαμανολιουδάκης, Νικόλαος | |
dc.coverage.spatial | Κύπρος | el_GR |
dc.date.accessioned | 2017-11-23T09:07:04Z | |
dc.date.available | 2017-11-23T09:07:04Z | |
dc.date.copyright | 2017 | |
dc.date.issued | 2017 | |
dc.identifier.other | ΠΕΣ/2017/00274 | el_GR |
dc.identifier.uri | http://hdl.handle.net/11128/3217 | |
dc.description | Includes bibliographical references. | el_GR |
dc.description.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. | el_GR |
dc.format.extent | 47 σ. 30 εκ. | el_GR |
dc.language | en | el_GR |
dc.language.iso | en | el_GR |
dc.publisher | Ανοικτό Πανεπιστήμιο Κύπρου | el_GR |
dc.rights | info:eu-repo/semantics/closedAccess | el_GR |
dc.subject | Machine learning | el_GR |
dc.title | Machine learning algorithms comparison | el_GR |
dc.type | Μεταπτυχιακή Διατριβή | el_GR |
dc.description.translatedabstract | ------- | el_GR |
dc.format.type | pdf | el_GR |