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News and Organization

News and OrganizationEDAN20 – Language Technology

Latest News

2024-08-23Registration
You should formally register in the LADOK system, preferably before the course starts. You have the instructions here in Swedish and in English. If you fail to register, the department might register you anyway, if you attended the first lecture and if you meet the prerequisites.
2024-08-23Please register to a laboratory group here: https://sam.cs.lth.se/LabsSelectSession?occasionId=884.
2024-08-23The first lecture will be given on Monday, September 2, 13-15.
2024-08-23There can be last minute changes in the timetable that do not show on the course web pages. Please always check the official times here: https://cloud.timeedit.net/lu/web/lth1/ri1Q5006.html
2024-08-23The course pages are provisional. They will be updated regularly.

Course Description

The course introduces theories and techniques of language technology and natural language processing. It focuses on industrial or laboratory applications, such as document retrieval on the internet, information extraction, and conversational agents. Fundamental algorithms will be described using Python, NumPy, or PyTorch.

Schedule

The course extends over the LP1 "study period".

For a detailed timetable of the lectures and labs, please visit this page: https://cloud.timeedit.net/lu/web/lth1/ri1Q5006.html and enter the course code: EDAN20.

Personnel

Passing the Course

To pass the course, you must carry out and validate all the programming assignments and hand in all the individual lab reports. You will then obtain a mark of 3. You can sit the optional examination to improve your mark to a 4 or a 5.

TypeNumber
Report on Python programming1Obligatory
Programming assignments6Obligatory
Individual lab reports6Obligatory
Examination1Optional

Course Literature

As textbook, I will use: Python for Natural Language Processing, 2024, Springer. It is available from Springer Link: https://link.springer.com/book/10.1007/978-3-031-57549-5.

You can access the book from the catalogue of Lund University Libraries: https://lubcat.lub.lu.se/. Once connected, you can download the PDF or read the chapters online.

Other references of interest include:

  • Steven Bird, Ewan Klein, and Edward Loper, Natural Language Processing with Python---Analyzing Text with the Natural Language Toolkit, O'Reilly, 2009. An on-line version of this book as well as many programs and corpora are available from the http://www.nltk.org/ site.
  • Daniel Jurafsky and James H. Martin, Speech and Language Processing, 2nd ed., Prentice Hall, 2008. They are preparing a 3rd edition available here: https://web.stanford.edu/~jurafsky/slp3/.
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