An introduction to proofs and the axiomatic methods through a study of the vector space axioms. Linear analytic geometry. Linear dependence and independence, subspaces, basis. Inner products. Matrix ...

The mathematics behind artificial intelligence (AI) and machine learning (ML) rely on linear algebra, calculus, probability, ...

Representation theory transforms abstract algebra groups into things like simpler matrices. The field’s ... redraw a ring or group as a less complex linear algebra structure, and then they ...

Introduces ordinary differential equations, systems of linear equations, matrices, determinants, vector spaces, linear transformations, and systems of linear differential equations. Prereq., APPM 1360 ...

This is in the flavour of MatLab. For those interested in using linear algebra in a symbolic setting, or for working with matrices over the integers or rational numbers (not float point numbers) ...

A range of basic mathematical concepts and methods in calculus of one and several variables and in linear algebra are covered and some applications ... unconstrained optimisation and Lagrange's method ...

Linear transformations. Linear operators, change of basis, inner product and the diagonalization problem. Quadratic forms. Convex sets and geometric programming, input/output models for an economy, ...

You will review the foundational mathematics that are critical in data science. Topics include algebra, calculus, linear algebra, and some pertinent numerical analysis. This specialization is also an ...