Lectures related to Vector Subspaces: Construction and Properties

Covers elementary matrix operations and vector spaces, including properties and conditions for invertibility.

Covers the definitions and properties of vector spaces, including axioms and examples.

Covers linear applications between vector spaces, exploring their properties and uniqueness based on bases.

Covers the basics of vector spaces, including operational definitions, properties, examples in RN, inner products, norms, and distances.

Explores subspaces in linear algebra and transformations, including kernels and images of linear transformations.

Explores vector equations, linear systems, and combinations in the context of linear algebra.

Covers matrix kernels, images, linear applications, independence, and bases in vector spaces.

Covers the concept of 3D vector space, scalar product, bases, orthogonality, and projections.