Concept

Vectorization (mathematics)

Related lectures (13)

Taylor Polynomials: Order 1

Covers the development of Taylor polynomials of order 1 and introduces related terminology and concepts.

Matlab: Interactive Mode and Project Steps

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

Matlab Functions: Vectorization and Plotting

Covers the 'find' function in Matlab for testing criteria on vectors or matrices.

Change of Basis: Matrices and Transformations

Explores changing bases in vector spaces using matrices and the significance of preserving structure within vector spaces.

Linear Quantum Calculus in Dirac Notation

Covers linear algebra in Dirac notation, emphasizing the scalar product and density product in quantum computations.

Vector Spaces: Operations and Properties

Explores vector spaces, scalar products, standards, and symmetric matrices in the context of operations and properties.

Numpy Tutorial

Covers the basics of Numpy, including importing the library, creating arrays, and performing linear algebra operations.

Vectorization in Python: Efficient Computation with Numpy

Covers vectorization in Python using Numpy for efficient scientific computing, emphasizing the benefits of avoiding for loops and demonstrating practical applications.

Partial Derivatives: Matrices and Local Extrema

Covers hessian matrices, positive definite matrices, and local extrema of functions.

Vector Differentiation and Convex Functions

Covers the concepts of vector differentiation and convex functions.

Vector Equations: Linear Combinations

Covers echelon matrices, vector equations, linear combinations, and vector spans in R^n.

Matricizations and Alternating Least Squares

Covers matricizations, ALS method, and tensor decomposition, emphasizing the alignment of fibers in matrices.

Advanced Analysis II: Derivatives and Notations

Covers derivatives, notations, composition of functions, and multiple derivatives in advanced analysis.