Lectures related to Vector and matrix operations

Introduces vector definitions, displacement, addition, and applications in geometry.

Covers linear equations, vectors, and matrices, exploring their fundamental concepts and applications.

Covers the fundamentals of analytical geometry, focusing on vectors and their operations.

Explores linear transformations, matrices, kernels, and images in algebra.

Explores vector space operations, linear transformations, matrix representation, and linear applications.

Introduces mechanics, differential and vector calculus, and historical perspectives from Aristotle to Newton.

Introduces abstract concepts in linear algebra, focusing on operations with vectors and matrices.

Introduces Matlab basics, error handling, and billiards project concepts.

Covers reducing matrices, uniqueness of row-echelon form, and identifying points using vectors.

Covers matrix operations, definitions, properties, and vector operations in Rn, essential for understanding linear algebra concepts.

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

Explores linear combinations of vectors and matrices in Rn, demonstrating geometric interpretations and matrix operations.

Covers advanced physics topics such as definitions, rectilinear motion, vectors, and motion in three dimensions.

Explains the construction of U, verification of results, and interpretation of SVD in matrix decomposition.

Covers the definition and properties of vector spaces, along with examples like Euclidean spaces and matrix spaces.

Covers calculations in coordinates for vectors, including bases, scalar product, and determinants, with geometric interpretations and examples.

Covers vector components, projections, conventions, operations, and mathematical identities.

Introduces vector spaces, subspaces, linear maps, and evaluation maps, with examples and exercises for better comprehension.

Explores matrix operations, linear systems, solutions, and the span of vectors in linear algebra.

Covers linear applications, matrices, transformations, and the principle of superposition.