Lectures related to Scalar (mathematics)

Covers the definition and properties of the scalar product, including geometric interpretations and algebraic properties.

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

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

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

Introduces the concept of vector spaces and covers properties of vectorial subspaces.

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

Explores the definition and properties of vector subspaces in linear algebra.

Explores orthogonality, scalar product, and orthonormal bases in vector spaces.

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

Explores Goldstone bosons and the Higgs mechanism, revealing how spontaneous symmetry breaking generates mass for gauge bosons.

Explores the properties of linear transformations through step-by-step calculations and matrix manipulations.

Explores the properties and applications of the dot product in vector spaces.

Explores dynamic programming with a focus on optimizing Matrix Chain Multiplication.

Covers the structure of vector spaces in R2 and R3, focusing on scalar multiplication and addition.

Introduces linear combinations in vector spaces, operations, and polynomials of degree 2.

Explains the concept of scalar product, its properties, and geometric interpretation.

Introduces scalars and vectors, explaining their properties and mathematical operations.

Explores optimal substructure and recursive formula in matrix chain multiplication using dynamic programming.

Introduces matrix algebra operations and their properties, including commutativity and distributivity.

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