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 ...

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 asynchronous online bridge course is specifically designed to help students satisfy the linear algebra admissions requirements for Michigan Tech's Online MS in Applied Statistics, an innovative ...

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

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 ...

One more patch (or hardcoded hack, rather) later the ‘Hello World’ example in Fortran was up and running, clearing the way to build the BLAS (Basic Linear Algebra Subprograms) and LAPACK ...

I ended up taking a Ph.D. class in numerical linear algebra. Again, the professor in that class took some interest in me, offered me a research project, and that’s how I started working on ...

This course develops ideas first presented in MA100. It consists of the linear algebra part of MA212, covering the following topics: Vector spaces and dimension. Linear transformations, kernel and ...

or in price calculations for financial options Tasks such as solving linear systems, computing eigenvectors and eigenvalues of large matrices, solving linear regression problems, often form the core ...

A range of basic mathematical concepts and methods in calculus of one and several variables and in linear algebra are covered and some applications illustrated. It is an essential pre-requisite for ...