Course Details
Course Code (English)
*
Semester
*
Title (English)
*
Lecture Hours (Weekly)
ECTS Credits
*
Course Type (English)
Prerequisites (English)
Programming, Data Structures and Algorithms, Probability and Statistics, Linear Algebra, Machine Learning, Linguistics, Text Processing
Course URL (e.g., on e-class)
Learning Outcomes (English)
- Proficiency in various text representation models used in Natural Language Processing (NLP) and Information Retrieval (IR). - Ability to apply and utilize Bag of Words and tf-idf techniques for text representation and feature extraction. - Understanding the fundamentals of information retrieval and its various methods. - Mastery in using vector-space methods for information retrieval tasks. - Familiarity with evaluation metrics used in assessing the performance of information retrieval systems. - Understanding different language models used specifically in information retrieval. - Proficiency in various word representation models used in NLP tasks. - Ability to work with word embeddings like word2vec for semantic representation of words. - Understanding and practical knowledge of Transformer-based models such as BERT and GPT for language understanding and generation tasks. - Ability to apply NLP techniques in various application-specific contexts, such as sentiment analysis, text classification, or named entity recognition. - Understanding techniques used in content-based retrieval systems for multimedia data.
General Competencies (English)
Search, analysis and synthesis of data and information with the use of the assorted technologies Decision Making Independent work Team work Work at an interdisciplinary framework Promoting free, creative and deductive reasoning
Course Content (English)
Text representation models Bag of words, tf-idf Information retrieval Vector-space methods for IR Information retrieval evaluation metrics IR and language models Word representation models Word embeddings (word2vec) RNN-LSTM Transformers - BERT, GPT Application-specific NLP Content-based multimedia retrieval
Use of ICT (English)
eclass, presentations, coding examples
Is it elective?
Άγνωστο
Ναι
Όχι
Load within semester (Hours)
Lecture Hours
Lab Hours
Independent Study
*
Project Work
*
Lab Report
*