Semester:
6th
Course Type:
Elective Specialization courses (ΠΜ-E)
Track:
CS (Computer Science)
Code:
ΥΣ19
ECTS:
6
TEACHING HOURS per week
Theory:
3
Seminar:
1
Laboratory:
-
Specializations
Foundations of Computer Science (S1):
-
Data and Knowledge Management (S2):
B Βασικό
Software (S3):
-
Hardware and Architecture (S4):
-
Communications and Networking (S5):
-
Signal and Information Processing (S6):
-
Related Courses
Detailed Description
Course Content
The course concentrates on the study of deep learning techniques and their use in natural language processing.
Topics: introduction to machine learning, regression, perceptron, neural networks, backpropagation, deep neural network training, word vectors, word2vec and related models, language modeling and RNNs, vanishing gradients, LSTMs/GRUs, machine translation, seq2seq and attention, transformers, large language models (BERT, GPT family, GEMINI family etc.).
The programming exercises of the course are done using Python, SciKitLearn and PyTorch.
e-Class link