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Ders Tanımı

Ders Kodu Yarıyıl T+U Saat Kredi AKTS
MACHİNE LEARNİNG AND COMPUTER VİSİON APPLİCATİON BSM 512 0 3 + 0 3 6
Ön Koşul Dersleri
Önerilen Seçmeli Dersler
Dersin Dili Türkçe
Dersin Seviyesi Yüksek Lisans
Dersin Türü SECMELI
Dersin Koordinatörü Dr.Öğr.Üyesi SERAP KAZAN
Dersi Verenler Dr.Öğr.Üyesi SERAP KAZAN
Dersin Yardımcıları
Dersin Kategorisi
Dersin Amacı
Introduction to machine learning. Learning the terms and concepts. Construction and encoding of data.
Dersin İçeriği
Evaluation of hypothesis. Learning at artificial neural network and mixed systems. Productivity of learning and error analysis methods. Increasing the reliability at machine learning. Pattern recognition and classification systems. Feature extraction methods. Feature vectors and classification designs at signature, fingerprint, object recognition etc. Example applications about machine learning.
Dersin Öğrenme Çıktıları Öğretim Yöntemleri Ölçme Yöntemleri
1 - Learn teoric and technic basics of using artifical intelligence with electronic devices and mechanics 1 - 2 - 4 - 15 - 16 - A - C - D -
2 - Learn to design classificition system with neural networks. 1 - 2 - 4 - 15 - 16 - A - C - D -
3 - Learn to code and config 1 - 2 - 4 - 16 - A - C - D -
Öğretim Yöntemleri: 1:Lecture 2:Question-Answer 4:Drilland Practice 15:Problem Solving 16:Project Based Learning
Ölçme Yöntemleri: A:Testing C:Homework D:Project / Design

Ders Akışı

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Kaynaklar

Ders Notu
Ders Kaynakları

Döküman Paylaşımı


Dersin Program Çıktılarına Katkısı

No Program Öğrenme Çıktıları KatkıDüzeyi
1 2 3 4 5
1 ability to access wide and deep information with scientific researches in the field of Engineering, evaluate, interpret and implement the knowledge gained in his/her field of study X
2 ability to complete and implement “limited or incomplete data” by using the scientific methods. X
3 ability to consolidate engineering problems, develop proper method(s) to solve and apply the innovative solutions to them X
4 ability to develop new and original ideas and method(s), to develop new innovative solutions at design of system, component or process X
5 gain comprehensive information on modern techniques, methods and their borders which are being applied to engineering X
6 ability to design and apply analytical, modelling and experimental based research, analyze and interpret the faced complex issues during the design and apply process X
7 gain high level ability to define the required information and data X
8 ability to work in multi-disciplinary teams and to take responsibility to define approaches for complex situations X
9 systematic and clear verbal or written transfer of the process and results of studies at national and international environments X
10 aware of social, scientific and ethical values guarding adequacy at all professional activities and at the stage of data collection, interpretation and announcement X
11 aware of new and developing application of profession and ability to analyze and study on those applications X
12 ability to interpret engineering application’s social and environmental dimensions and it’s compliance with the social environment X

Değerlendirme Sistemi

YARIYIL İÇİ ÇALIŞMALARI SIRA KATKI YÜZDESİ
AraSinav 1 100
Toplam 100
Yıliçinin Başarıya Oranı 50
Finalin Başarıya Oranı 50
Toplam 100

AKTS - İş Yükü

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