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HU Credits:
3
Degree/Cycle:
1st degree (Bachelor)
Responsible Department:
Computer Sciences
Semester:
1st Semester
Teaching Languages:
Hebrew
Campus:
E. Safra
Course/Module Coordinator:
Omri Abend
Coordinator Office Hours:
Teaching Staff:
Prof Omri Abend
Course/Module description:
Natural Langue Processing (NLP) addresses the automatic analysis of text and speech, and interfaces with various fields such as formal languages, machine learning, linguistics and cognitive psychology. It also has a variety of applications, e.g., in machine translation, information retrieval, and human-computer interaction. The course will present the main challenges the field is facing and (mostly statistical) techniques for addressing them.
Course/Module aims:
Acquaintance with the main problems of the field, its existing capabilities and hands-on experience in implementing them.
Learning outcomes - On successful completion of this module, students should be able to:
Implement basic techniques in Natural Language Processing, and get a basic understanding of the current literature in the field.
Attendance requirements(%):
0
Teaching arrangement and method of instruction:
Oral presentations, accompanied by theoretical and programming exercises.
Course/Module Content:
1. Language models, smoothing and neural language models
2. Bag of words models
3. Log-linear models and feed-forward neural networks
4. Linear chain methods,
tagging, named entity recognition
5. Recurrent neural networks
6. Vector space models of semantics
7. Sentiment analysis
8. Syntactic parsing
9. Information extraction
10. Transformers and transfer learning
11. Machine translation
Required Reading:
--
Additional Reading Material:
https://web.stanford.edu/~jurafsky/slp3/
Grading Scheme :
Written / Oral / Practical Exam 70 %
Submission assignments during the semester: Exercises / Essays / Audits / Reports / Forum / Simulation / others 30 %
Additional information:
There will be four exercises (all mandatory). Some of them theoretical and some will involve programming.
(in standard years, there are five exercises)
This year the classes on transition-based parsing and introduction to grammar have been removed to accommodate for the shorter semester.
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