Introduces linear algebra and matrices, with an emphasis on applications, including methods to solve systems of linear algebraic and linear ordinary differential equations. Discusses computational ...

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 ...

This bridge course has a very practical curriculum, which covers the fundamentals of linear algebra as they are used in applied statistics courses. Some of the topics include, but are not limited to, ...

However, AI models are often used to find intricate patterns in data where the output is not always proportional to the input. For this, you also need non-linear thresholding functions that adjust the ...

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 ...

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, ...

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) ...

Introduces linear algebra and matrices with an emphasis on applications, including methods to solve systems of linear algebraic and linear ordinary differential equations. Discusses vector space ...