Bibliography and Supporting Materials

Book: 

• Deisenroth, M. P.; Faisal, A. A. & Ong, C. S. (2020), Mathematics for Machine Learning, Cambridge University Press.

• Solution guide (link).

Week 2 - Linear Algebra

Content: 

• Slides (link).

• Videos: 

  • Part 1 (link).

  • Part 2 (link).

  • Part 3 (link). Erratum: include Ex. 2.20 as a final exercise!

Assignments:

• • Proposed exercises: 2.6, 2.7, 2.8b, 2.3, 2.10, 2.12, 2.16c, 2.16d, 2.19, 2.20. Check the video to understand the suggested order. 

Week 4 - Matrix Decompositions

Content: 

• Slides (link).

• Videos: 

  • Part 1 (link).

  • Part 2 (link).

Assignments:

• Proposed exercises: 4.1, 4.3, 4.4, 4.7, 4.8, 4.9. Check the video to understand the suggested order. 

Week 6 - Probability and Distributions

Content: 

• Slides (link).

• Videos:

  • Part 1 (link).

  • Part 2 (link).

  • Part 3 (link).

    • Due to the questions regarding Sufficient Statistics, this video may help to complement the proper definition and intepretation.

  • Part 4 (Extra): Parameter Estimation with ML, MAP, and Bayesian approaches (link, tutorial).

Assignments:

• Proposed exercises: 6.1, 6.4, 6.2, 6.5, 6.12. Check the video to understand the suggested order. 

Week 8 - When Models Meet Data

Content: 

• Slides (link).

• Video (link).

Week 10 - Dimensionality Reduction with Principal Component Analysis

Content: 

• Slides (link).

• Videos

  • Part 1 (link).

  • Part 2 (link).

Assignments:

• Tutorial (link) - only Part 1!

• Solution (link).

Week 12 - Classification with Support Vector Machines

Content: 

• Slides (link).

• Videos

  • Part 1 (link).