Eigenvector University returns to Seattle May 15-20, 2022 Complete Info Here!

Linear Algebra for Machine Learning and Chemometrics

Course Description

It has been said that “linear algebra is the language of machine learning and chemometrics.” Linear Algebra for Machine Learning and Chemometrics provides the necessary mathematical background required to understand what’s going on “under the hood” of most machine learning methods, and makes chemometric literature accessible. This half-day course introduces concepts that are required for a complete understanding of common techniques such as Principal Components Analysis, Partial Least Squares Regression, Multivariate Curve Resolution and other machine learning methods.

Prerequisites

None, though this Primer On Linear Algebra is highly recommended.

Course Outline

  1. Definitions: scalar, vector, matrix
  2. Vector and matrix addition and multiplication
  3. Inner products and projections
  4. Outer products
  5. Solving systems of equations
  6. Matrix rank
  7. Least squares
  8. Ill-conditioned problems
  9. Singular Value Decomposition (SVD)