Eigenvalue and Eigenvector (Module6, Part 1) Introduction to Linear Algebra for Computer Science скачать в хорошем качестве

Eigenvalue and Eigenvector (Module6, Part 1) Introduction to Linear Algebra for Computer Science

This module will cover the following topics: 1- #Linear #Transformations 2- #Eigenvalues and #Eigenvectors 3- LU #Decomposition 4- #QR #Decomposition 5- #Eigendecomposition 6- #SVD #linearalgebra #computerscience These slides are based on the slides and the book entitled "Introduction to Applied Linear Algebra" by , Boyd & Vandenberghe, as well as the book entitled "Mathematics for Machine Learning" by Deisenroth, Faisal, and Ong. [1] Boyd, Stephen, and Lieven Vandenberghe. Introduction to applied linear algebra: vectors, matrices, and least squares. Cambridge university press, 2018. [2] Deisenroth, Marc Peter, A. Aldo Faisal, and Cheng Soon Ong. Mathematics for machine learning. Cambridge University Press, 2020.