Topic outline

  • About the course

    • Course description 2022/2023 File Uploaded 8/02/23, 16:47

    • 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).


    • Exams

        • First exam, June 9, 2023 at 12pm in P01
        • Second exam, June 21, 2023 at 11am in P22
        • Third exam, August 22, 2023 at 9am in P22

  • 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
      		 Revision of neural networks
      8
      		 Neural embeddings
      9 Convolutional and recurrent neural networks for text, ELMo
      10
      		 Attention mechanism and transformer networks
      11
      		 Large language models (BERT, GPT, T5 families) and multimodal models
      12
      		 POS-tagging, dependency parsing, named entity recognition and semantic role labelling
      13
      		 Word senses and disambiguation
      14
      		 Affective computing
      15
      		 Machine translation
      16
      		 Summarization and question answering
      17
      		 Knowledge graphs for commonsense reasoning
      18
      		 Guest lecture

    • The lecture recordings from 2020/21 are available in MS Teams, UL FRI NLP team, use the code sw6ukln for access.

  • Quizzes

  • Lab sessions

    Lab sessions will start in the second week of semester (February 20, 2023).