Skip to main content
Graph
Search
fr
en
Login
Search
All
Categories
Concepts
Courses
Lectures
MOOCs
People
Practice
Publications
Startups
Units
Show all results for
Home
Lecture
Oja's Rule
Graph Chatbot
Related lectures (29)
Previous
Page 1 of 3
Next
Principal Components: Properties & Applications
Explores principal components, covariance, correlation, choice, and applications in data analysis.
PCA: Derivation and Optimization
Covers the derivation of PCA projection, error minimization, and eigenvector optimization.
Multivariate Statistics: Wishart and Hotelling T²
Explores the Wishart distribution, properties of Wishart matrices, and the Hotelling T² distribution, including the two-sample Hotelling T² statistic.
Multivariate Statistics: Introduction and Methods
Introduces multivariate statistics, focusing on uncovering associations between components in data in vector form.
Eigenvalues and Eigenvectors in 3D
Explores eigenvalues and eigenvectors in 3D linear algebra, covering characteristic polynomials, stability under transformations, and real roots.
Principal Component Analysis: Olympic Medals & Image Compression
Explores PCA for predicting medals distribution and compressing face images.
Characteristic Polynomials and Similar Matrices
Explores characteristic polynomials, similarity of matrices, and eigenvalues in linear transformations.
Linear Algebra: Eigenvalues and Eigenvectors
Explores eigenvalues, eigenvectors, diagonalization, and spectral theorem in linear algebra.
Eigenvalues and Eigenvectors: Understanding Matrix Properties
Explores eigenvalues and eigenvectors, demonstrating their importance in linear algebra and their application in solving systems of equations.
Diagonalization of Linear Transformations
Explains the diagonalization of linear transformations using eigenvectors and eigenvalues to form a diagonal matrix.
