Real Vector Space: Basics

Related lectures (30)

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Explores the scalar product, vector lengths, angles, norms, and rotations in 2D and 3D spaces.

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

Covers matrix operations, scalar products, vector norms, and orthogonality in vector spaces.

Covers the geometric properties of the dot product and its algebraic aspects.

Explores conformity and compliancy in geometry, emphasizing angle preservation and function conditions.

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

Covers linear applications, diagonalizable matrices, eigenvectors, and orthogonal subspaces in R^n.

Explores pre-Hilbertian spaces, focusing on dot product properties and algebraic bases.

Covers normed vector spaces, including definitions, properties, examples, and sets in normed spaces.

Covers the properties of vectors, including commutativity, distributivity, and linearity.