Informatics 2B - Learning: Drop-in Labs

Note:

Demonstrator: Andreas Kapourani (Weeks 2-7)

  1. Week 02 (25 Jan.): Introduction to Matlab (1 and 2). (NB: 16:10-18:00) Lab 1, Lab 2
  2. Week 03 (01 Feb.): Similarity and recommender systems. Lab 3, and data.txt
  3. Week 04 (08 Feb.): K-means clustering and PCA. Lab 4 and [faithful.txt]
  4. Week 05 (15 Feb.): K-NN classification and Statistical pattern recognition. Lab 5 (ver 2.0. Updated on 27 Feb.) and [fish.txt], [lemon-orange.txt]
  5. Week 06 (01 Mar.): Naive Bayes and Introduction to Gaussians. Lab 6
  6. Week 07 (08 Mar.): Classification with Gaussians. Lab 7
  7. Week 08 (15 Mar.): Coursework 2
  8. Week 09 (22 Mar.): Coursework 2
  9. Week 10 (29 Mar.): Coursework 2
  10. Week 11 (Tue, 04 Apr.) at 16:30-18:30: Coursework 2


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