Lectures related to Operations with Linear Applications

Covers orthogonality, scalar products, orthogonal bases, and vector projection in detail.

Covers the properties and operations of vector spaces, including addition and scalar multiplication.

Covers linear algebra in Dirac notation, focusing on vector spaces and quantum bits.

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

Covers matrices, linear applications, vector spaces, and bijective functions.

Explores orthogonality between vectors and subspaces, demonstrating practical implications in matrix operations.

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

Covers the basics of linear algebra, emphasizing the identification of subspaces through key properties.

Introduces the kernel of a linear application and its properties.

Covers linear independence, bases, and coordinate systems with examples and theorems.