Topic outline

  • About the course

    • Course is held in English.

    • Course description 2021/2022 File Uploaded 13/02/22, 21:40

    • Honor Code

      We encourage students to form study groups, and discuss the lecture and other materials. However, the work that you submit should be your own work. For the programming part you are allowed to use other solutions, algorithms but you must know their properties and also introduce your own contributions for completion of your project (e.g. input data manipulation, parameter changes, architectural changes).


    • Communication

      The main communication channel for this course are Discord channels. If you ask a question that might be relevant to your colleagues privately (via private Discord message, Moodle message, e-mail, etc.), you might not get answered. Use private means of communications only when really necessary. You are always welcome to come by to our offices:

        • Full Prof. Dr. Marko Robnik-Šikonja @ R2.06 (lecturer)
        • Assist. Prof. Dr. Slavko Žitnik @ R2.58 (assistant)

    • Exams

        • First exam, June 3, 2022, 15:00 @ FRI PA
        • Second exam, June 21, 2022, 9:00 @ FRI P01
        • Third exam, August 16, 2022, 9:00 @ FRI P01

  • Lectures

    • The course syllabus.

      Topic
      		 Lectures
      1
      		 Syllabus and obligations
      2 Language and intelligence, a short overview of NLP
      3
      		 Text normalization
      4 Regular expressions and context-free grammars
      5
      		 Edit distance and document similarity
      6
      		 Sparse and dense word representations
      7
      		 Statistical n-gram language models
      8
      		 Revision of neural networks
       9 Neural embeddings
      10
      		 Convolutional and recurrent neural networks for text 
      11
      		 ELMo, attention, transformer networks, BERT models
      12
      		 POS-tagging, dependency parsing, and named entity recognition
      13
      		 Word senses and disambiguation
      14
      		 Affective computing
      15
      		 Machine translation
      16
      		 Summarization and question answering
      17
      		 Guest lecture

    • The lecture recordings are available in MS Teams, UL FRI NLP team, use the code sw6ukln for access.

  • Quizzes

  • Lab sessions

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