Informatics 2B - Learning: Drop-in Labs

Note:

Demonstrators: Ioannis Chalkiadakis (Monday sessions), Caesar Zhang (Tuesday sessions)

Schedule:

  1. Week 02 (21,22 Jan.): Introduction to Matlab. Lab 1 Part 1 and Part 2
  2. Week 03 (28,29 Jan.): Similarity and recommender systems. Lab 2, and data.txt
  3. Week 04 (04,05 Feb.): K-means clustering and PCA. Lab 3, and data sets: faithful.txt, iris.txt
  4. Week 05 (11,12 Feb.): K-NN classification. Lab 4 and [lemon-orange.txt]
  5. Week 06 (25,26 Feb.): Statistical pattern recognition. Lab 5 and [fish.txt]
  6. Week 07 (04,05 Mar.): Naive Bayes and Introduction to Gaussians. Lab 6
  7. Week 08 (11,12 Mar.): Classification with Gaussians. Lab 7
  8. Week 09 (Mon,18/Mar:12:30-13:30, Tue,19/Mar:11:10-13:00): CW2 drop-in labs
  9. Week 10 (TBC): CW2 drop-in labs
  10. Week 11 (TBC): CW2 drop-in labs


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