PRE2: Mathematics for Datascience


Université Paris-Saclay, Master in Artificial Intelligence

Home

Schedule&Material

References

Schedule


This page presents the curriculum of the class and the material for the lectures.

Beware tough that the course will be taught mostly on a (virtual) whiteboard. Hence you are expected to be as much active for the course than for a real course taught on a real board.

You should take handwritten notes of the class otherwise you will not be able to do the exercices and work on the examples (so do not forget to have papers and pen with you to attend the class).

You are encouraged to ask questions if you do not understand the content (or my writting!) ...



Date Topics Material
Thursday, 10.9.2020 Vector space: vectors, norms, linear independence, span, basis, linear transformations Exercices, Organization, Class Notes
Thursday, 17.09.2020 matrix (matrix operations, link to linear transformations) - rank, kernel, inverse Class Notes
Thursday, 24.09.2020 Dot products, orthogonality, transpose, orthogonal matrices, solving linear systems, norms Exercices, Class Notes
Thursday, 1.10.2020 Eigenvalues and matrix diagonalization, Gram matrices, Spectral theorem, polar decomposition, trace, matrix norm Exercices, Class Notes
Thursday, 8.10.2020 Singular Value Decomposition, determinant Class Notes
Thursday, 15.10.2020 Multivariate Calculus Class Notes
Thursday, 22.10.2020 Final exam Instructions - How to register for exam
Last updated: Mon, 19 Oct 2020 10:19