Course Information

Course Name	Turkish	Doğal Dil İşlemede İleri Konular
	English	Advanced Methods in Natural Language Processing
Course Code	BLG 621	Credit	Lecture (hour/week)	Recitation (hour/week)	Laboratory (hour/week)
Semester	2	3	3	-	-
Course Language		Turkish
Course Coordinator		Gülşen Eryiğit
Course Objectives		1. to introduce statistical approaches used in natural language processing and understanding 2. to introduce machine learning approaches used in natural language processing and understanding 3. to introduce deep learning approaches used in natural language processing and understanding 4. to introduce evaluation methods used in the performance evaluation of natural Language Processing models
Course Description		Statistical methods (T-test, X2 test and mutual information) used in NLP, Hiddden Markov Models, Maximum Entropy Models, Conditional Random Fields , NLP architectures, Support Vector Machines, neural language models, textual representations, text classification, sequence labeling, encoder-decoder models, attention mechanisms, transformers. NLP tasks and their modeling
Course Outcomes		Ph.D. students who successfully pass this course gain knowledge, skill and competency in the following subjects; 1. The students will learn the fundamentals of statistical natural language processing. 2. The students will learn how to handle a natural language processing problem as a machine learning task. 3. The students will be informed about modern machine learning methods used in natural language processing. 4. The students will be informed about modern textual representations and deep learning methods used in natural language processing.
Pre-requisite(s)		Machine Learning, Deep Learning, Statistics, Introduction to NLP
Required Facilities
Other
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