Course Information

Course Name	Turkish	Doğal Dil İşleme
	English	Natural Language Processing
Course Code	YZV 405E	Credit	Lecture (hour/week)	Recitation (hour/week)	Laboratory (hour/week)
Semester	6	3	3	-	-
Course Language		English
Course Coordinator		Gülşen Eryiğit
Course Objectives		To introduce the students with the fundamental techniques and current research topics in the field of natural language processing. Improving human-computer interaction using NLP techniques Machine translation using NLP techniques Information extraction using NLP techniques
Course Description		NLP stages and their interaction, NLP tasks, statistical language models, neural language models, text representations, sequence labeling, encoder-decoder models, attention mechanisms, transformers.
Course Outcomes		The students will learn the main layers and tasks in natural language processing (nlp). The students will learn the fundamental approaches in different nlp layers. The students will learn the main differences between rule based, statistical, ML and DL techniques in nlp. The students will learn the basic rule-based approaches in nlp. The students will learn the basic statistical approaches in nlp. The students will learn the basic machine learning approaches in nlp. The students will learn the basic deep learning approaches in nlp.
Pre-requisite(s)		YZV 302E MIN DD or YZV 303E MIN DD
Required Facilities
Other
Textbook		Jurafsky, D., Martin, J. H., 2022. Speech and language processing : An Introduction to Natural Language Processing, computational linguistics, and speech recognition (3rd ed.), Prentice Hall.
Other References		Manning, C., Schütze, H., 1999. Foundations of Statistical Natural Language Processing, MIT Press. Cambridge, MA. Allen, J., 1995. Natural Language Understanding , Second edition, The Benjamin/Cumings Publishing Company Inc. Ranchod, E., Mamede, N. J., 2002. Advances in Natural Language Processing, Springer-Verlag.

Courses

Help

About