{"id":1604,"date":"2023-03-26T23:17:36","date_gmt":"2023-03-26T20:17:36","guid":{"rendered":"https:\/\/www.ict.ihu.gr\/?post_type=course&#038;p=1604"},"modified":"2024-12-02T18:22:47","modified_gmt":"2024-12-02T16:22:47","slug":"%cf%80%ce%bb%cf%8505052","status":"publish","type":"course","link":"https:\/\/www.ict.ihu.gr\/en\/courses\/%cf%80%ce%bb%cf%8505052\/","title":{"rendered":"Computational Intelligence"},"author":7,"template":"","meta":{"_acf_changed":false},"semester":[38],"course_type":[13],"acf":{"code":"\u03a0\u039b\u03a505052","semester":38,"level":"1","teaching_activities":{"activity_1":{"description":"Lectures","weekly_hrs":2,"ects":5},"activity_2":{"description":"Practice Exercises","weekly_hrs":1,"ects":""},"activity_3":{"description":"Laboratory Exercises","weekly_hrs":1,"ects":""},"activity_4":{"description":"","weekly_hrs":"","ects":""},"activity_5":{"description":"","weekly_hrs":"","ects":""}},"type":13,"language":"Greek","erasmus":"\u038c\u03c7\u03b9","url":"http:\/\/teachers.cm.ihu.gr\/strch\/apnd.pdf","prerequisites":"","instructors":[1405],"coordinator":"","content":"\u0395\u0399\u03a3\u0391\u0393\u03a9\u0393\u0397\r\n<ul>\r\n \t<li>\u0391\u03c0\u03b1\u03c1\u03b1\u03af\u03c4\u03b7\u03c4\u03b5\u03c2 \u039c\u03b1\u03b8\u03b7\u03bc\u03b1\u03c4\u03b9\u03ba\u03ad\u03c2 \u03ad\u03bd\u03bd\u03bf\u03b9\u03b5\u03c2 \u03ba\u03b1\u03b9 \u03b5\u03c1\u03b3\u03b1\u03bb\u03b5\u03af\u03b1.<\/li>\r\n \t<li>\u039c\u03b5\u03c4\u03c1\u03b9\u03ba\u03ad\u03c2 \u03ba\u03b1\u03b9 \u03b1\u03c0\u03bf\u03c3\u03c4\u03ac\u03c3\u03b5\u03b9\u03c2.<\/li>\r\n<\/ul>\r\n\u03a4\u0391\u039e\u0399\u039d\u039f\u039c\u0397\u03a3\u0397 \u039c\u0395 \u0395\u03a0\u039f\u03a0\u03a4\u0397\r\n<ul>\r\n \t<li>\u039f \u03b1\u03bb\u03b3\u03cc\u03c1\u03b9\u03b8\u03bc\u03cc\u03c2 \u03c4\u03c9\u03bd k \u03ba\u03bf\u03bd\u03c4\u03b9\u03bd\u03cc\u03c4\u03b5\u03c1\u03c9\u03bd \u03b3\u03b5\u03b9\u03c4\u03cc\u03bd\u03c9\u03bd (knn).<\/li>\r\n \t<li>\u03a4\u03b1\u03be\u03b9\u03bd\u03cc\u03bc\u03b7\u03c3\u03b7 \u03bc\u03b5 \u03b3\u03c1\u03b1\u03bc\u03bc\u03b9\u03ba\u03ad\u03c2 \u03b4\u03b9\u03b1\u03ba\u03c1\u03b9\u03c4\u03b9\u03ba\u03ad\u03c2 \u03c3\u03c5\u03bd\u03b1\u03c1\u03c4\u03ae\u03c3\u03b5\u03b9\u03c2.<\/li>\r\n \t<li>\u039f Perceptron.<\/li>\r\n \t<li>\u03a3\u03c5\u03bd\u03b1\u03c1\u03c4\u03ae\u03c3\u03b5\u03b9\u03c2 \u03b5\u03bd\u03b5\u03c1\u03b3\u03bf\u03c0\u03bf\u03af\u03b7\u03c3\u03b7\u03c2.<\/li>\r\n \t<li>O \u03c0\u03bf\u03bb\u03c5\u03b5\u03c0\u03af\u03c0\u03b5\u03b4\u03bf\u03c2 Perceptron (Multi-Layer Perceptron).<\/li>\r\n \t<li>\u039c\u03b7 \u03b3\u03c1\u03b1\u03bc\u03bc\u03b9\u03ba\u03cc\u03c4\u03b7\u03c4\u03b1 \u03bc\u03b5 \u03c3\u03b9\u03b3\u03bc\u03bf\u03b5\u03b9\u03b4\u03b5\u03af\u03c2 \u03c3\u03c5\u03bd\u03b1\u03c1\u03c4\u03ae\u03c3\u03b5\u03b9\u03c2.<\/li>\r\n \t<li>\u03a3\u03c5\u03bd\u03ac\u03c1\u03c4\u03b7\u03c3\u03b7 \u03ba\u03cc\u03c3\u03c4\u03bf\u03c5\u03c2 \u03bc\u03ad\u03c3\u03bf\u03c5 \u03c4\u03b5\u03c4\u03c1\u03b1\u03b3\u03c9\u03bd\u03b9\u03ba\u03bf\u03cd \u03c3\u03c6\u03ac\u03bb\u03bc\u03b1\u03c4\u03bf\u03c2.<\/li>\r\n \t<li>\u0392\u03b5\u03bb\u03c4\u03b9\u03c3\u03c4\u03bf\u03c0\u03bf\u03af\u03b7\u03c3\u03b7 \u03bc\u03b5 \u03ba\u03ac\u03b8\u03bf\u03b4\u03bf \u03ba\u03b1\u03c4\u03ac \u03c4\u03b7\u03bd \u03ba\u03bb\u03af\u03c3\u03b7 (Gradient Descent).<\/li>\r\n \t<li>\u0394\u03b9\u03cc\u03c1\u03b8\u03c9\u03c3\u03b7 \u03bc\u03b5 \u03c4\u03b7\u03bd \u03bc\u03ad\u03b8\u03bf\u03b4\u03bf \u03c4\u03b7\u03c2 \u03bf\u03c0\u03b9\u03c3\u03b8\u03bf\u03b4\u03b9\u03ac\u03b4\u03bf\u03c3\u03b7\u03c2 \u00a0\u03c3\u03c6\u03ac\u03bb\u03bc\u03b1\u03c4\u03bf\u03c2 (Back error propagation).<\/li>\r\n \t<li>\u03a3\u03c5\u03bd\u03b5\u03bb\u03b9\u03ba\u03c4\u03b9\u03ba\u03ac \u039d\u03b5\u03c5\u03c1\u03c9\u03bd\u03b9\u03ba\u03ac \u0394\u03af\u03ba\u03c4\u03c5\u03b1 (CNN), Deep Learning.<\/li>\r\n \t<li>M\u03b7 \u03b3\u03c1\u03b1\u03bc\u03bc\u03b9\u03ba\u03cc\u03c4\u03b7\u03c4\u03b1 \u03bc\u03b5 \u03c4\u03b9\u03c2 \u03c3\u03c5\u03bd\u03b1\u03c1\u03c4\u03ae\u03c3\u03b5\u03b9\u03c2 ReLU \u03ba\u03b1\u03b9 Softmax.<\/li>\r\n \t<li>\u0397 \u03a3\u03c5\u03bd\u03ac\u03c1\u03c4\u03b7\u03c3\u03b7 \u03ba\u03cc\u03c3\u03c4\u03bf\u03c5\u03c2 cross-entropy.<\/li>\r\n \t<li>\u0392\u03b5\u03bb\u03c4\u03b9\u03c3\u03c4\u03bf\u03c0\u03bf\u03b9\u03b7\u03c4\u03ad\u03c2 (optimizers) (SGD, Batch GD, Momentum GD, ADAM \u03ba\u03bb\u03c0).<\/li>\r\n \t<li>\u03a3\u03b7\u03bc\u03b1\u03c3\u03b9\u03bf\u03bb\u03bf\u03b3\u03b9\u03ba\u03ae \u03ba\u03b1\u03c4\u03ac\u03c4\u03bc\u03b7\u03c3\u03b7 \u03b5\u03b9\u03ba\u03cc\u03bd\u03c9\u03bd \u03bc\u03b5 CNN.<\/li>\r\n \t<li>\u0391\u03bd\u03b1\u03b4\u03c1\u03bf\u03bc\u03b9\u03ba\u03ac \u039d\u03b5\u03c5\u03c1\u03c9\u03bd\u03b9\u03ba\u03ac \u0394\u03af\u03ba\u03c4\u03c5\u03b1 RNN \u03ba\u03b1\u03b9 LSTM.<\/li>\r\n \t<li>\u0394\u03ad\u03bd\u03b4\u03c1\u03b1 \u03b1\u03c0\u03cc\u03c6\u03b1\u03c3\u03b7\u03c2<\/li>\r\n<\/ul>\r\n\u0395\u039a\u03a0\u0391\u0399\u0394\u0395\u03a5\u03a3\u0397 \u03a7\u03a9\u03a1\u0399\u03a3 \u0395\u03a0\u039f\u03a0\u03a4\u0397\r\n<ul>\r\n \t<li>\u0391\u03c0\u03b5\u03b9\u03ba\u03cc\u03bd\u03b9\u03c3\u03b7 \u03b1\u03bb\u03c5\u03c3\u03af\u03b4\u03b1\u03c2.<\/li>\r\n \t<li>\u039f \u0391\u03bb\u03b3\u03cc\u03c1\u03b9\u03b8\u03bc\u03bf\u03c2 ISODATA \u03ae \u039a-\u039c\u03ad\u03c3\u03c9\u03bd (k-means \u03ae c-means).<\/li>\r\n \t<li>\u0391\u03c5\u03c4\u03bf-\u03bf\u03c1\u03b3\u03b1\u03bd\u03bf\u03cd\u03bc\u03b5\u03bd\u03bf\u03b9 \u03c0\u03af\u03bd\u03b1\u03ba\u03b5\u03c2 \u03b1\u03c0\u03b5\u03b9\u03ba\u03cc\u03bd\u03b9\u03c3\u03b7\u03c2 \u03c7\u03b1\u03c1\u03b1\u03ba\u03c4\u03b7\u03c1\u03b9\u03c3\u03c4\u03b9\u03ba\u03ce\u03bd \u03c4\u03bf \u039d\u03b5\u03c5\u03c1\u03c9\u03bd\u03b9\u03ba\u03cc \u03b4\u03af\u03ba\u03c4\u03c5\u03bf Kohonen.<\/li>\r\n<\/ul>\r\n\u0391\u039d\u0391\u039b\u03a5\u03a3\u0397 \u03a7\u0391\u03a1\u0391\u039a\u03a4\u0397\u03a1\u0399\u03a3\u03a4\u0399\u039a\u03a9\u039d\r\n<ul>\r\n \t<li>\u0391\u03bd\u03ac\u03bb\u03c5\u03c3\u03b7 \u03c7\u03b1\u03c1\u03b1\u03ba\u03c4\u03b7\u03c1\u03b9\u03c3\u03c4\u03b9\u03ba\u03ce\u03bd \u03c3\u03c4\u03b7\u03bd \u03b5\u03ba\u03c0\u03b1\u03af\u03b4\u03b5\u03c5\u03c3\u03b7 \u03bc\u03b5 \u03b5\u03c0\u03cc\u03c0\u03c4\u03b7.<\/li>\r\n \t<li>\u0391\u03bd\u03ac\u03bb\u03c5\u03c3\u03b7 \u03c7\u03b1\u03c1\u03b1\u03ba\u03c4\u03b7\u03c1\u03b9\u03c3\u03c4\u03b9\u03ba\u03ce\u03bd \u03c3\u03c4\u03b7\u03bd \u03b5\u03ba\u03c0\u03b1\u03af\u03b4\u03b5\u03c5\u03c3\u03b7 \u03c7\u03c9\u03c1\u03af\u03c2 \u03b5\u03c0\u03cc\u03c0\u03c4\u03b7, \u0391\u03bd\u03ac\u03bb\u03c5\u03c3\u03b7 \u039a\u03cd\u03c1\u03b9\u03c9\u03bd \u03a3\u03c5\u03bd\u03b9\u03c3\u03c4\u03c9\u03c3\u03ce\u03bd (Principal Component Analysis).<\/li>\r\n<\/ul>","goals":"\u03a3\u03c4\u03bf \u03bc\u03ac\u03b8\u03b7\u03bc\u03b1 \u03c0\u03b1\u03c1\u03bf\u03c5\u03c3\u03b9\u03ac\u03b6\u03bf\u03bd\u03c4\u03b1\u03b9 \u03bf\u03b9 \u03b8\u03b5\u03bc\u03b5\u03bb\u03b9\u03ce\u03b4\u03b5\u03b9\u03c2 \u03ad\u03bd\u03bd\u03bf\u03b9\u03b5\u03c2 \u03c4\u03b7\u03c2 \u03a5\u03c0\u03bf\u03bb\u03bf\u03b3\u03b9\u03c3\u03c4\u03b9\u03ba\u03ae\u03c2 \u039d\u03bf\u03b7\u03bc\u03bf\u03c3\u03cd\u03bd\u03b7\u03c2 \u03bc\u03b5 \u03b1\u03c0\u03ce\u03c4\u03b5\u03c1\u03bf \u03c3\u03ba\u03bf\u03c0\u03cc \u03c4\u03b7\u03bd \u03ba\u03b1\u03c4\u03b1\u03bd\u03cc\u03b7\u03c3\u03b7 \u03c4\u03c9\u03bd \u03c4\u03b5\u03c7\u03bd\u03bf\u03bb\u03bf\u03b3\u03b9\u03ba\u03ce\u03bd \u03b5\u03c6\u03b1\u03c1\u03bc\u03bf\u03b3\u03ce\u03bd \u03ba\u03b1\u03b9 \u03b5\u03c0\u03b9\u03c4\u03b5\u03c5\u03b3\u03bc\u03ac\u03c4\u03c9\u03bd \u03c0\u03bf\u03c5 \u03b2\u03b1\u03c3\u03af\u03b6\u03bf\u03bd\u03c4\u03b1\u03b9 \u03c3\u03c4\u03bf \u03c3\u03c5\u03b3\u03ba\u03b5\u03ba\u03c1\u03b9\u03bc\u03ad\u03bd\u03bf \u03b5\u03c0\u03b9\u03c3\u03c4\u03b7\u03bc\u03bf\u03bd\u03b9\u03ba\u03cc \u03ba\u03ac\u03b4\u03bf. \u0397 \u03a5\u03c0\u03bf\u03bb\u03bf\u03b3\u03b9\u03c3\u03c4\u03b9\u03ba\u03ae \u039d\u03bf\u03b7\u03bc\u03bf\u03c3\u03cd\u03bd\u03b7 \u03ba\u03c5\u03c1\u03b9\u03b1\u03c1\u03c7\u03b5\u03af \u03c3\u03c4\u03b7\u03bd \u03bc\u03b5\u03c4\u03ac\u03b2\u03b1\u03c3\u03b7 \u03b1\u03c0\u03cc \u03c4\u03b9\u03c2 \u03ad\u03be\u03c5\u03c0\u03bd\u03b5\u03c2 \u03bc\u03b7\u03c7\u03b1\u03bd\u03ad\u03c2 \u03c3\u03c4\u03b9\u03c2 \u03bd\u03bf\u03ae\u03bc\u03bf\u03bd\u03b5\u03c2. \u039f\u03b9 \u03c3\u03c0\u03bf\u03c5\u03b4\u03b1\u03c3\u03c4\u03ad\u03c2 \u03b4\u03b9\u03b4\u03ac\u03c3\u03ba\u03bf\u03bd\u03c4\u03b1\u03b9 \u03c4\u03b9\u03c2 \u03b2\u03b1\u03c3\u03b9\u03ba\u03ad\u03c2 \u03ad\u03bd\u03bd\u03bf\u03b9\u03b5\u03c2, \u03c4\u03b1 \u03bc\u03b1\u03b8\u03b7\u03bc\u03b1\u03c4\u03b9\u03ba\u03ac \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03b1 \u03ba\u03b1\u03b9\u00a0 \u03c4\u03b9\u03c2 \u03bc\u03b5\u03b8\u03cc\u03b4\u03bf\u03c5\u03c2 \u03c4\u03bf\u03c5 \u03ba\u03bb\u03ac\u03b4\u03bf\u03c5. \u0393\u03bd\u03c9\u03c1\u03af\u03b6\u03bf\u03c5\u03bd \u03c4\u03b9\u03c2 \u03c0\u03c1\u03bf\u03ba\u03bb\u03ae\u03c3\u03b5\u03b9\u03c2 \u03c4\u03bf\u03c5 \u03c7\u03ce\u03c1\u03bf\u03c5 \u03ba\u03b1\u03b9 \u03b1\u03c0\u03bf\u03ba\u03c4\u03bf\u03cd\u03bd \u03c4\u03bf \u03b2\u03b1\u03c3\u03b9\u03ba\u03cc \u03c5\u03c0\u03cc\u03b2\u03b1\u03b8\u03c1\u03bf \u03b3\u03b9\u03b1 \u03c0\u03b5\u03c1\u03b1\u03b9\u03c4\u03ad\u03c1\u03c9 \u03b5\u03c0\u03b9\u03c3\u03c4\u03b7\u03bc\u03bf\u03bd\u03b9\u03ba\u03cc \u03ba\u03b1\u03b9 \u03b5\u03c1\u03b5\u03c5\u03bd\u03b7\u03c4\u03b9\u03ba\u03cc \u03ad\u03c1\u03b3\u03bf. \u0397 \u03b5\u03ba\u03c0\u03b1\u03b9\u03b4\u03b5\u03c5\u03c4\u03b9\u03ba\u03ae \u03b4\u03b9\u03b1\u03b4\u03b9\u03ba\u03b1\u03c3\u03af\u03b1 \u03bf\u03bb\u03bf\u03ba\u03bb\u03b7\u03c1\u03ce\u03bd\u03b5\u03c4\u03b1\u03b9 \u03bc\u03b5 \u03c4\u03b7\u03bd \u03b5\u03ba\u03bc\u03ac\u03b8\u03b7\u03c3\u03b7 \u03ba\u03b1\u03b9 \u03c7\u03c1\u03ae\u03c3\u03b7 \u00a0\u03bb\u03bf\u03b3\u03b9\u03c3\u03bc\u03b9\u03ba\u03bf\u03cd \u03b5\u03c1\u03b3\u03b1\u03c3\u03c4\u03b7\u03c1\u03b9\u03b1\u03ba\u03ac.","skills":"<ul>\r\n \t<li>\u039a\u03b1\u03c4\u03b1\u03bd\u03cc\u03b7\u03c3\u03b7 \u03c4\u03bf\u03c5 \u03c3\u03c4\u03cc\u03c7\u03bf\u03c5 \u03c4\u03bf\u03c5 \u03b5\u03c0\u03b9\u03c3\u03c4\u03b7\u03bc\u03bf\u03bd\u03b9\u03ba\u03bf\u03cd \u03ba\u03bb\u03ac\u03b4\u03bf\u03c5 \u03ba\u03b1\u03b9 \u03c4\u03c9\u03bd \u03b5\u03c6\u03b1\u03c1\u03bc\u03bf\u03b3\u03ce\u03bd \u03c0\u03bf\u03c5 \u03bc\u03c0\u03bf\u03c1\u03bf\u03cd\u03bd \u03bd\u03b1 \u03b5\u03c0\u03b9\u03c4\u03b5\u03c5\u03c7\u03b8\u03bf\u03cd\u03bd \u03b2\u03ac\u03c3\u03b5\u03b9 \u03b1\u03c5\u03c4\u03bf\u03cd.<\/li>\r\n \t<li>\u03a3\u03c7\u03b5\u03b4\u03b9\u03b1\u03c3\u03bc\u03cc\u03c2 \u03ba\u03b1\u03b9 \u0394\u03b9\u03b1\u03c7\u03b5\u03af\u03c1\u03b9\u03c3\u03b7 \u0388\u03c1\u03b3\u03c9\u03bd.<\/li>\r\n \t<li>\u03a0\u03c1\u03bf\u03b1\u03b3\u03c9\u03b3\u03ae \u03c4\u03b7\u03c2 \u03b5\u03bb\u03b5\u03cd\u03b8\u03b5\u03c1\u03b7\u03c2, \u03b4\u03b7\u03bc\u03b9\u03bf\u03c5\u03c1\u03b3\u03b9\u03ba\u03ae\u03c2 \u03ba\u03b1\u03b9 \u03b5\u03c0\u03b1\u03b3\u03c9\u03b3\u03b9\u03ba\u03ae\u03c2 \u03c3\u03ba\u03ad\u03c8\u03b7\u03c2.<\/li>\r\n<\/ul>","teaching_methods":"<ul>\r\n \t<li>\u0398\u03b5\u03c9\u03c1\u03b7\u03c4\u03b9\u03ba\u03ae \u03b1\u03c0\u03cc \u03ad\u03b4\u03c1\u03b1\u03c2 \u03b4\u03b9\u03b4\u03b1\u03c3\u03ba\u03b1\u03bb\u03af\u03b1 \u03bc\u03b5 \u03c3\u03c5\u03b6\u03ae\u03c4\u03b7\u03c3\u03b7 \u03ba\u03b1\u03b9 \u03b5\u03bd\u03b5\u03c1\u03b3\u03ae \u03c3\u03c5\u03bc\u03bc\u03b5\u03c4\u03bf\u03c7\u03ae \u03c4\u03c9\u03bd \u03c6\u03bf\u03b9\u03c4\u03b7\u03c4\u03ce\u03bd. \u039a\u03b1\u03c4\u03ac \u03c4\u03b7\u03bd \u03b4\u03b9\u03ac\u03c1\u03ba\u03b5\u03b9\u03b1 \u03c4\u03bf\u03c5 \u03bc\u03b1\u03b8\u03ae\u03bc\u03b1\u03c4\u03bf\u03c2 \u03b3\u03af\u03bd\u03bf\u03bd\u03c4\u03b1\u03b9 \u03c0\u03b1\u03c1\u03bf\u03c5\u03c3\u03b9\u03ac\u03c3\u03b5\u03b9\u03c2 \u03c3\u03b5 powerpoint.<\/li>\r\n \t<li>\u03a0\u03b1\u03c1\u03bf\u03c5\u03c3\u03af\u03b1\u03c3\u03b7 \u03b5\u03c6\u03b1\u03c1\u03bc\u03bf\u03b3\u03ce\u03bd \u03ba\u03b1\u03b9 \u03c0\u03b1\u03c1\u03b1\u03b4\u03b5\u03b9\u03b3\u03bc\u03ac\u03c4\u03c9\u03bd \u03bc\u03b5 \u03c7\u03c1\u03ae\u03c3\u03b7 \u03bb\u03bf\u03b3\u03b9\u03c3\u03bc\u03b9\u03ba\u03bf\u03cd.<\/li>\r\n<\/ul>","ict_usage":"<ul>\r\n \t<li>\u03a7\u03c1\u03ae\u03c3\u03b7 \u03b5\u03be\u03b5\u03b9\u03b4\u03b9\u03ba\u03b5\u03c5\u03bc\u03ad\u03bd\u03bf\u03c5 \u03bb\u03bf\u03b3\u03b9\u03c3\u03bc\u03b9\u03ba\u03bf\u03cd.<\/li>\r\n \t<li>\u03a5\u03c0\u03bf\u03c3\u03c4\u03ae\u03c1\u03b9\u03be\u03b7 \u039c\u03b1\u03b8\u03b7\u03c3\u03b9\u03b1\u03ba\u03ae\u03c2 \u03b4\u03b9\u03b1\u03b4\u03b9\u03ba\u03b1\u03c3\u03af\u03b1\u03c2 \u03bc\u03ad\u03c3\u03c9 \u03c4\u03b7\u03c2 \u03b7\u03bb\u03b5\u03ba\u03c4\u03c1\u03bf\u03bd\u03b9\u03ba\u03ae\u03c2 \u03c0\u03bb\u03b1\u03c4\u03c6\u03cc\u03c1\u03bc\u03b1\u03c2 e-class.<\/li>\r\n \t<li>\u0391\u03c3\u03ba\u03ae\u03c3\u03b5\u03b9\u03c2 \u0391\u03c5\u03c4\u03bf\u03b1\u03be\u03b9\u03bf\u03bb\u03cc\u03b3\u03b7\u03c3\u03b7\u03c2.<\/li>\r\n<\/ul>","teaching_organization":{"activity_1":{"description":"Lectures","workload":26},"activity_2":{"description":"Practice Exercises","workload":13},"activity_3":{"description":"Laboratory Exercises","workload":13},"activity_4":{"description":"Autonomous Study","workload":52},"activity_5":{"description":"Teamwork","workload":21},"activity_6":{"description":"","workload":""}},"students_evaluation":"\u039f \u03b2\u03b1\u03b8\u03bc\u03cc\u03c2 \u03c4\u03bf\u03c5 \u03b8\u03b5\u03c9\u03c1\u03b7\u03c4\u03b9\u03ba\u03bf\u03cd \u03bc\u03ad\u03c1\u03bf\u03c5\u03c2 \u03b4\u03b9\u03b1\u03bc\u03bf\u03c1\u03c6\u03ce\u03bd\u03b5\u03c4\u03b1\u03b9 \u03b1\u03c0\u03cc \u03b3\u03c1\u03b1\u03c0\u03c4\u03ae \u03c4\u03b5\u03bb\u03b9\u03ba\u03ae \u03b5\u03be\u03ad\u03c4\u03b1\u03c3\u03b7. \u0397 \u03b3\u03c1\u03b1\u03c0\u03c4\u03ae \u03c4\u03b5\u03bb\u03b9\u03ba\u03ae \u03b5\u03be\u03ad\u03c4\u03b1\u03c3\u03b7 \u03c4\u03bf\u03c5\u03bc\u03b1\u03b8\u03ae\u03bc\u03b1\u03c4\u03bf\u03c2 \u03c0\u03b5\u03c1\u03b9\u03bb\u03b1\u03bc\u03b2\u03ac\u03bd\u03b5\u03b9:\r\n<ul>\r\n \t<li>\u0395\u03c0\u03af\u03bb\u03c5\u03c3\u03b7 \u03c0\u03c1\u03bf\u03b2\u03bb\u03b7\u03bc\u03ac\u03c4\u03c9\u03bd \u03b5\u03c6\u03b1\u03c1\u03bc\u03bf\u03b3\u03ae\u03c2 \u03c4\u03c9\u03bd \u03b3\u03bd\u03ce\u03c3\u03b5\u03c9\u03bd \u03c0\u03bf\u03c5 \u03b1\u03c0\u03bf\u03ba\u03c4\u03ae\u03b8\u03b7\u03ba\u03b1\u03bd.<\/li>\r\n \t<li>\u0395\u03c1\u03c9\u03c4\u03ae\u03c3\u03b5\u03b9\u03c2 \u03c3\u03cd\u03bd\u03c4\u03bf\u03bc\u03b7\u03c2 \u03b1\u03c0\u03ac\u03bd\u03c4\u03b7\u03c3\u03b7\u03c2.<\/li>\r\n<\/ul>","bib_textbooks":"\u03a3\u03c5\u03b3\u03b3\u03c1\u03ac\u03bc\u03bc\u03b1\u03c4\u03b1 \u03bc\u03ad\u03c3\u03c9 \u03c4\u03bf\u03c5 \u03c3\u03c5\u03c3\u03c4\u03ae\u03bc\u03b1\u03c4\u03bf\u03c2 \u0395\u03a5\u0394\u039f\u039e\u039f\u03a3:\r\n<ol>\r\n \t<li>\u0392\u03b9\u03b2\u03bb\u03af\u03bf [13256974]: \u0391\u03bd\u03b1\u03b3\u03bd\u03ce\u03c1\u03b9\u03c3\u03b7 \u03a0\u03c1\u03bf\u03c4\u03cd\u03c0\u03c9\u03bd, Theodoridis S.<\/li>\r\n \t<li>\u0392\u03b9\u03b2\u03bb\u03af\u03bf [9743]: \u039d\u03b5\u03c5\u03c1\u03c9\u03bd\u03b9\u03ba\u03ac \u0394\u03af\u03ba\u03c4\u03c5\u03b1 &amp; \u039c\u03b7\u03c7\u03b1\u03bd\u03b9\u03ba\u03ae \u039c\u03ac\u03b8\u03b7\u03c3\u03b7, Haykin Simon.<\/li>\r\n \t<li>\u0392\u03b9\u03b2\u03bb\u03af\u03bf [13908]: \u03a4\u0395\u03a7\u039d\u0397\u03a4\u0391 \u039d\u0395\u03a5\u03a1\u03a9\u039d\u0399\u039a\u0391 \u0394\u0399\u039a\u03a4\u03a5\u0391, \u039a\u03a9\u039d\u03a3\u03a4\u0391\u039d\u03a4\u0399\u039d\u039f\u03a3 \u0394\u0399\u0391\u039c\u0391\u039d\u03a4\u0391\u03a1\u0391\u03a3.<\/li>\r\n<\/ol>\r\n\u03a3\u03c5\u03b3\u03b3\u03c1\u03ac\u03bc\u03bc\u03b1\u03c4\u03b1 \u03c0\u03bf\u03c5 \u03b4\u03b9\u03b1\u03bd\u03ad\u03bc\u03bf\u03bd\u03c4\u03b1\u03b9 \u03bc\u03ad\u03c3\u03c9 \u03c4\u03bf\u03c5 \u0399\u03b4\u03c1\u03cd\u03bc\u03b1\u03c4\u03bf\u03c2 \u03ae \u03c4\u03b7\u03c2 \u03b7\u03bb\u03b5\u03ba\u03c4\u03c1\u03bf\u03bd\u03b9\u03ba\u03ae\u03c2 \u03c3\u03b5\u03bb\u03af\u03b4\u03b1\u03c2 \u03c4\u03bf\u03c5 \u03bc\u03b1\u03b8\u03ae\u03bc\u03b1\u03c4\u03bf\u03c2:\r\n<ol>\r\n \t<li>\u03a7.\u03a3\u03a4\u03a1\u039f\u03a5\u0398\u039f\u03a0\u039f\u03a5\u039b\u039f\u03a3 \u00ab\u03a5\u03a0\u039f\u039b\u039f\u0393\u0399\u03a3\u03a4\u0399\u039a\u0397 \u039d\u039f\u0397\u039c\u039f\u03a3\u03a5\u039d\u0397\u00bb \u03a3\u0397\u039c\u0395\u0399\u03a9\u03a3\u0395\u0399\u03a3.<\/li>\r\n<\/ol>\r\n\u03a3\u03c5\u03bc\u03c0\u03bb\u03b7\u03c1\u03c9\u03bc\u03b1\u03c4\u03b9\u03ba\u03ae \u03c0\u03c1\u03bf\u03c4\u03b5\u03b9\u03bd\u03cc\u03bc\u03b5\u03bd\u03b7 \u03b2\u03b9\u03b2\u03bb\u03b9\u03bf\u03b3\u03c1\u03b1\u03c6\u03af\u03b1:\r\n<ol>\r\n \t<li>Judith Dayhott, \u201cNeural Network Architectures\u201d, VAN NOSTRAND REINHOLD, ISBN: 0-442-20744-1.<\/li>\r\n<\/ol>","bib_journals":""},"_links":{"self":[{"href":"https:\/\/www.ict.ihu.gr\/en\/wp-json\/wp\/v2\/course\/1604"}],"collection":[{"href":"https:\/\/www.ict.ihu.gr\/en\/wp-json\/wp\/v2\/course"}],"about":[{"href":"https:\/\/www.ict.ihu.gr\/en\/wp-json\/wp\/v2\/types\/course"}],"author":[{"embeddable":true,"href":"https:\/\/www.ict.ihu.gr\/en\/wp-json\/wp\/v2\/users\/7"}],"version-history":[{"count":21,"href":"https:\/\/www.ict.ihu.gr\/en\/wp-json\/wp\/v2\/course\/1604\/revisions"}],"predecessor-version":[{"id":4102,"href":"https:\/\/www.ict.ihu.gr\/en\/wp-json\/wp\/v2\/course\/1604\/revisions\/4102"}],"acf:post":[{"embeddable":true,"href":"https:\/\/www.ict.ihu.gr\/en\/wp-json\/wp\/v2\/staff\/1405"}],"acf:term":[{"embeddable":true,"taxonomy":"course_type","href":"https:\/\/www.ict.ihu.gr\/en\/wp-json\/wp\/v2\/course_type\/13"},{"embeddable":true,"taxonomy":"semester","href":"https:\/\/www.ict.ihu.gr\/en\/wp-json\/wp\/v2\/semester\/38"}],"wp:attachment":[{"href":"https:\/\/www.ict.ihu.gr\/en\/wp-json\/wp\/v2\/media?parent=1604"}],"wp:term":[{"taxonomy":"semester","embeddable":true,"href":"https:\/\/www.ict.ihu.gr\/en\/wp-json\/wp\/v2\/semester?post=1604"},{"taxonomy":"course_type","embeddable":true,"href":"https:\/\/www.ict.ihu.gr\/en\/wp-json\/wp\/v2\/course_type?post=1604"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}