UPF Master in Bioinformatics 2016-2017
eduardo.eyras [at] upf.edu
- 0. Description of the course (Slides)
- 1. Vector spaces, basis and dimension.
- 2. Linear maps
- 3. Linear maps and matrices.
- 4. Projections and Subspaces
- 5. Matrices, determinants, eigenvalues and diagonalization.
- 6. Singular Value Decomposition (SVD) and Principal Components Analysis (PCA).
- 7. Many-valued functions and optimization.
- 8. Gradient, level surfaces and tangent hyperplanes.
- 9. Optimization with constraints.
- 10. Linear decision hyperplanes and Support Vector Machines.
Homework (to be delivered by Monday, December 5h) (Homework)
December 14th, 11am-1pm (aula 61.325-61.327)
Material and bibliography