Informatics 2B: Lecture Schedule

Semester 2

NB: From 24 Mar 2020, 'flipped classroom' is held via the Balckboard Collaborate system. Please have a look at lecture notes and slides to prepare your questions.

Notes and slides are linked from this page. Slides are given both as "full" (one slide per page, easier to view on a screen) and as "multi" (typically 4 or 6 per page, saves on paper if printed).

Merged versions of all notes and all slides: all-notes, all-notes-multi all-slides, all-slides-multi.

Lecture recordings: Lectures are recorded automatically. The recordings can be accessed by logging in to Learn. Currently it is not possible to supply direct links from this page.
Pre-recorded lectures are available from Learn for Lectures 14,15 and 16.

  1. Tue, 14 Jan: Introduction to learning and data. (Chapter 1; slides-fullslides-multi; Matlab, Python)

  2. Tue, 21 Jan: Similarity and recommender systems. (Chapter 2; slides-fullslides-multi)

  3. Tue, 28 Jan: Clustering and data visualisation. (Chapter 3; slides-fullslides-multi)

  4. Tue, 04 Feb: Classification and nearest neighbours. (Chapter 4; slides-fullslides-multi)
  5. Fri, 07 Feb: Introduction to statistical pattern recognition and optimisation. (Chapter 5; slides-fullslides-multi)

  6. Tue, 11 Feb: Naive Bayes classification. (Chapter 6; slides-fullslides-multi)
  7. Fri, 14 Feb: Text classification using Naive Bayes. (Chapter 7; slides-fullslides-multi)

    17-21 Feb, Flexible Learning Week, no lectures or tutorials

  8. Tue, 25 Feb: Gaussians. (Chapter 8; slides-fullslides-multi)
  9. Fri, 28 Feb: Classification with Gaussians. (Chapter 9; slides-fullslides-multi)

  10. Tue, 03 Mar: Discriminant functions. (Chapter 10; slides-fullslides-multi)
  11. Fri, 06 Mar: Single-layer neural networks 1. (slides-fullslides-multi)

  12. Tue, 10 Mar: Single-layer neural networks 2. (Chapter 11; slides-fullslides-multi)
  13. Fri, 13 Mar: Single layer neural networks 3. (Chapter 11; slides-fullslides-multi)

  14. Tue, 24 Mar:Multi-layer neural networks 1. (Chapter 12; slides-fullslides-multi) [Online session] (Pre-recorded lecture available from Learn)
  15. Fri, 27 Mar: Multi-layer neural networks 2. (Chapter 12; slides-fullslides-multi) [Online session] (Pre-recorded lecture available from Learn)
  16. Tue, 31 Mar: Review and conclusion of learning thread. (slides-fullslides-multi) [Online session] (Pre-recorded lecture available from Learn)

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