Linear Algebra: Spanning and Combining Vectors

Related lectures (24)

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

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

Explores linear dependence and independence of vectors in geometric spaces.

Explores vector spaces, subspaces, bases, and linear combinations in R² and R³, including free and linked families.

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

Covers vector equations, linear combinations, and the span of vectors.

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

Explores vector spaces in three dimensions, covering linear combinations, subspaces, and properties of families of vectors in R³.

Introduces algebraic properties, vector equations, and matrix operations.

Covers vector spaces, subspaces, kernel, image, linear independence, and bases in linear algebra.