Bilgisayar Mühendisliği

CE 455 | Ders Tanıtım Bilgileri

Dersin Adı

Deep Neural Networks

Kodu	Yarıyıl	Teori (saat/hafta)	Uygulama/Lab (saat/hafta)	Yerel Kredi	AKTS
CE 455	FALL	3	0	3	5

Ön-Koşul(lar)	Array
Dersin Dili	English
Dersin Türü	ELECTIVE_COURSE
Dersin Düzeyi	Lisans
Dersin Veriliş Şekli	Face-To-Face
Dersin Öğretim Yöntem ve Teknikleri	Problem Solving Lecture / Presentation
Ulusal Meslek Sınıflandırma Kodu	-
Dersin Koordinatörü	Dr. Öğr. Üyesi Kaya Oğuz
Öğretim Eleman(lar)ı	-
Yardımcı(ları)	-

Dersin Amacı

This course provides advanced knowledge about the structures and algorithms of advanced deep neural networks. The theoretical properties of deep neural networks structures and algorithms, as well as practical applications resulting from this theory will be discussed.

Öğrenme Çıktıları

Bu dersi başarıyla tamamlayabilen öğrenciler;

Ad	Açıklama	PC Alt	* Katkı Düzeyi
Ad	Açıklama	PC Alt	1	2	3	4	5
LO1	describe deep neural network structures and models.	1.5				X
LO2	use general structures and algorithms in the field of deep neural networks.	1.6				X
LO3	compare different algorithms in the field of deep learning.	2				X
LO4	apply various deep neural network algorithms to specific problems.	3.1				X
LO5	develop deep neural network models and algorithms using computer toolboxes.	4				X

Ders Tanımı

The course content includes feedforward neural networks, backpropagation, convolutional neural networks, recurrent neural networks, reversible neural networks, regularization, and optimization.

Dersin İlişkili Olduğu Sürdürülebilir Kalkınma Amaçları

Dersin Kategorisi	Temel Ders
	Uzmanlık/Alan Dersleri	X
	Destek Dersleri
	İletişim ve Yönetim Becerileri Dersleri
	Aktarılabilir Beceri Dersleri

HAFTALIK KONULAR VE İLGİLİ ÖN HAZIRLIK ÇALIŞMALARI

Hafta	Konular	Ön Hazırlık	Öğrenme Çıktısı
1	Introduction	Bölüm 1. Deep Learning. I. Goodfellow, Y. Bengio, A. Courville. ISBN: 9780262035613.	LO1
2	Applied Math and Machine Learning Basics	Bölüm 2-3. Deep Learning. I. Goodfellow, Y. Bengio, A. Courville. ISBN: 9780262035613.	LO3
3	Applied Math and Machine Learning Basics	Bölüm 4-5. Deep Learning. I. Goodfellow, Y. Bengio, A. Courville. ISBN: 9780262035613.	LO1
4	Deep Feedforward Networks	Bölüm 6. Deep Learning. I. Goodfellow, Y. Bengio, A. Courville. ISBN: 9780262035613.	LO2
5	Regularization for Deep Learning	Bölüm 7. Deep Learning. I. Goodfellow, Y. Bengio, A. Courville. ISBN: 9780262035613.	LO2
6	Regularization for Deep Learning	Bölüm 7. Deep Learning. I. Goodfellow, Y. Bengio, A. Courville. ISBN: 9780262035613.	LO2
7	Optimization for Deep Models	Bölüm 8. Deep Learning. I. Goodfellow, Y. Bengio, A. Courville. ISBN: 9780262035613.	LO2
8	Midterm Exam		-
9	Optimization for Deep Models	Bölüm 8. Deep Learning. I. Goodfellow, Y. Bengio, A. Courville. ISBN: 9780262035613.	LO2
10	Convolutional Neural Networks	Bölüm 9. Deep Learning. I. Goodfellow, Y. Bengio, A. Courville. ISBN: 9780262035613.	LO4
11	Convolutional Neural Networks	Bölüm 9. Deep Learning. I. Goodfellow, Y. Bengio, A. Courville. ISBN: 9780262035613.	LO4
12	Recurrent and Recursive Nets	Bölüm 10 Deep Learning. I. Goodfellow, Y. Bengio, A. Courville. ISBN: 9780262035613.	LO4
13	Recurrent and Recursive Nets	Bölüm 10 Deep Learning. I. Goodfellow, Y. Bengio, A. Courville. ISBN: 9780262035613.	LO4
14	Practical Methodology and Applications	Bölüm 11-12. Deep Learning. I. Goodfellow, Y. Bengio, A. Courville. ISBN: 9780262035613.	LO5
15	Review of the Semester		-
16	Final Exam		-

Ders Kitabı	I. Goodfellow Y. Bengio A. Courville Deep Learning MIT Press 2016 ISBN: 9780262035613.
Önerilen Okumalar/Materyaller	-

DEĞERLENDİRME ÖLÇÜTLERİ

Yarıyıl Aktiviteleri	Sayı	Katkı Payı %	LO1	LO2	LO3	LO4	LO5
Küçük Sınav / Stüdyo Kritiği	4	20	X	X	X	X
Proje	1	10				X	X
Ara Sınav	1	30	X	X	X
Final Sınavı	1	40	X	X	X	X	X
Toplam	7	100

AKTS / İŞ YÜKÜ TABLOSU

Yarıyıl Aktiviteleri	Sayı	Süre (Saat)	İş Yükü
Katılım	-	-	-
Teorik Ders Saati	16	3	48
Laboratuvar / Uygulama Ders Saati	-	-	-
Sınıf Dışı Ders Çalışması	14	3	42
Arazi Çalışması	-	-	-
Küçük Sınav / Stüdyo Kritiği	4	3	12
Portfolyo	-	-	-
Ödev	-	-	-
Sunum / Jüri Önünde Sunum	-	-	-
Proje	1	8	8
Seminer/Çalıştay	-	-	-
Sözlü Sınav	-	-	-
Ara Sınavlar	1	15	15
Final Sınavı	1	25	25
		Toplam	150

DERSİN ÖĞRENME ÇIKTILARININ PROGRAM YETERLİLİKLERİ İLE İLİŞKİSİ

#	PC Alt	Program Yeterlilikleri / Çıktıları	* Katkı Düzeyi
#	PC Alt	Program Yeterlilikleri / Çıktıları	1	2	3	4	5
1	Engineering Knowledge: Knowledge of mathematics, science, basic engineering, computation, and related engineering discipline-specific topics; the ability to apply this knowledge to solve complex engineering problems.
	1	Mathematics
	2	Science
	3	Basic Engineering
	4	Computation
	5	Related engineering discipline-specific topics				LO1
	6	The ability to apply this knowledge to solve complex engineering problems				LO2
2	Problem Analysis: Ability to identify, formulate and analyze complex engineering problems using basic knowledge of science, mathematics and engineering, and considering the UN Sustainable Development Goals relevant to the problem being addressed.					LO3
3	Engineering Design: The ability to devise creative solutions to complex engineering problems; the ability to design complex systems, processes, devices or products to meet current and future needs, considering realistic constraints and conditions.
	1	Ability to design creative solutions to complex engineering problems				LO4
	2	Ability to design complex systems, processes, devices or products to meet current and future needs, considering realistic constraints and conditions
4	Use of Techniques and Tools: Ability to select and use appropriate techniques, resources, and modern engineering and computing tools, including estimation and modeling, for the analysis and solution of complex engineering problems, while recognizing their limitations.					LO5
5	Research and Investigation: Ability to use research methods to investigate complex engineering problems, including literature research, designing and conducting experiments, collecting data, and analyzing and interpreting results.
	1	Literature research for the study of complex engineering problems
	2	Designing experiments
	3	Ability to use research methods, including conducting experiments, collecting data. analyzing and interpreting results
6	Global Impact of Engineering Practices: Knowledge of the impacts of engineering practices on society, health and safety, economy, sustainability, and the environment, within the context of the UN Sustainable Development Goals; awareness of the legal implications of engineering solutions.
	1	Knowledge of the impacts of engineering practices on society, health and safety, economy, sustainability, and the environment, within the context of the UN Sustainable Development Goals
	2	Awareness of the legal implications of engineering solutions
7	Ethical Behavior: Acting in accordance with the principles of the engineering profession, knowledge about ethical responsibility; awareness of being impartial, without discrimination, and being inclusive of diversity.
	1	Acting in accordance with the principles of the engineering profession, knowledge about ethical responsibility ethical responsibility
	2	Awareness of being impartial and inclusive of diversity, without discriminating on any subject
8	Individual and Teamwork: Ability to work effectively, individually and as a team member or leader on interdisciplinary and multidisciplinary teams (face-to-face, remote or hybrid).
	1	Ability to work individually and within the discipline
	2	Ability to work effectively as a team member or leader in multidisciplinary teams (face-to-face, remote or hybrid)
9	Verbal and Written Communication: Taking into account the various differences of the target audience (such as education, language, profession) on technical issues.
	1	Ability to communicate verbally
	2	Ability to communicate effectively in writing
10	Project Management: Knowledge of business practices such as project management and economic feasibility analysis; awareness of entrepreneurship and innovation.
	1	Knowledge of business practices such as project management and economic feasibility analysis
	2	Awareness of entrepreneurship and innovation
11	Lifelong Learning: Lifelong learning skills that include being able to learn independently and continuously, adapting to new and developing technologies, and thinking questioningly about technological changes.

*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest

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Lisansüstü Programları Doktora Programları

CE 455 | Ders Tanıtım Bilgileri

HAFTALIK KONULAR VE İLGİLİ ÖN HAZIRLIK ÇALIŞMALARI

DEĞERLENDİRME ÖLÇÜTLERİ

AKTS / İŞ YÜKÜ TABLOSU

DERSİN ÖĞRENME ÇIKTILARININ PROGRAM YETERLİLİKLERİ İLE İLİŞKİSİ

HABERTÜM HABERLER

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İZMİR EKONOMİ ÜNİVERSİTESİ GÜZELBAHÇE KAMPÜSÜ

KÜRESEL KARİYER

BİLİME KATKI

İNSANA DEĞER

TOPLUMA FAYDA