linear transformations, and inner product spaces. This is the official course description: A course in linear algebra that studies the fundamentals of vector spaces, inner product spaces, and linear ...

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, ...

It consists of the linear algebra part of MA212, covering the following topics: Vector spaces and dimension. Linear transformations, kernel and image. Real inner products. Orthogonal matrices, and the ...

Vector spaces, linear transformation, matrix representation, inner product spaces, isometries, least squares, generalised inverse, eigen theory, quadratic forms, norms, numerical methods. The fourth ...

linear transformations, and systems of linear differential equations. Prereq., APPM 1360 or MATH 2300 (min. grade C-). Credit not granted for this course and both MATH 3130 and 4430. Usually offered ...

A range of basic mathematical concepts and methods in calculus of one and several variables and in linear algebra are covered and some applications ... basis and dimension, Linear transformations ...

Additionally, students must always refer to course syllabus for the most up to date information. Introduces the fundamentals of linear algebra in the context of computer science applications. Includes ...

These pages provide a showcase of how to use Python to do computations from linear algebra. We will demonstrate both the NumPy (SciPy) and SymPy packages. This is meant to be a companion guide to a ...