MIT - A 2020 Vision of Linear Algebra, Spring 2020
Professor Strang presents a fresh approach to linear algebra, focusing on matrices. This concise series covers key concepts like column space, orthogonality, eigenvalues, and solving linear systems.
Linear Algebra
In this course, you will learn systems of linear equations, Matrices, Elementary row operations, Row-reduced echelon matrices. Vector spaces, Subspaces, Bases and dimension, Ordered bases and coordinates.
Linear Algebra
Comprehensive exploration of linear algebra concepts, from basic operations to advanced topics like eigenvalues, with practical applications and problem-solving techniques.
Applied Linear Algebra
Explore vector spaces, linear maps, eigenvalues, and applications in systems, algorithms, and optimization. Gain practical skills in linear algebra for various fields.
Face Recognition Techniques and Applications - Lecture 14
Explore face recognition techniques, from simple approaches to advanced methods like PCA and Linear Discriminant Analysis. Learn about eigenvectors, image compression, and scatter matrices.
Facial Recognition: Eigenvectors and Covariance Matrices - Lecture 14
Explore facial recognition technology, from simple approaches to advanced techniques using eigenvectors and covariance matrices. Learn about challenges and solutions in this field.
Linear Algebra
Comprehensive exploration of linear algebra concepts, from basic matrix operations to complex numbers, with practical examples and geometric applications.
A Second Course in Differential Equations
Explore advanced topics in ordinary differential equations, including linear systems, eigenvalues, numerical methods, and Python implementations for solving complex ODEs.
Linear Algebra - Vol 2
Explore advanced linear algebra concepts including transformation matrices, determinants, cofactors, eigenvalues, and eigenvectors through comprehensive lessons and practical examples.
Grade 11 Maths - Matrices
Explore matrices, determinants, and their applications in solving systems of equations, including Cramer's rule, for Ethiopian Grade 11 mathematics.
Linear Algebra
Comprehensive exploration of linear algebra concepts, from matrices and vector spaces to eigenvalues and transformations, with practical applications and in-depth explanations.
Linear Algebra for Quantum Mechanics
Explore essential linear algebra concepts for quantum mechanics, including linear transformations, eigenvectors, and Hermitian operators, enhancing your understanding of mathematical formalism in quantum physics.
Systems of Differential Equations - Diagonalization and Jordan Canonical Form
Explore diagonalization and Jordan Canonical Form for systems of differential equations, covering eigenvectors, complex conjugates, repeated eigenvalues, and general matrix applications.
Non-Normal Linear Systems and Transient Energy Growth - Bypass Transition to Turbulence
Explore non-normal linear systems and their role in turbulence, including examples, code demonstrations, and applications in fluid dynamics and bypass transition.
Drawing Phase Portraits for Nonlinear Systems
Learn to analyze nonlinear systems by drawing phase portraits, identifying fixed points, linearizing, and inferring global dynamics. Gain practical skills in stability analysis using eigenvalues and eigenvectors.
Systems of ODEs: Imaginary Eigenvalues and Center Fixed Points
Explore imaginary eigenvalues and center fixed points in 2D ODE systems. Learn to compute eigenvectors, write solutions, and understand geometric intuition behind rotational dynamics.
Systems of ODEs - Saddle Points and Instability
Explore unstable saddle points in 2D linear ODEs, their applications in energy-efficient transport, and analysis using eigenvalues, eigenvectors, and phase portraits.
Eigenvalues and Eigenvectors
Explore eigenvalues and eigenvectors, key concepts in linear algebra. Learn to compute them for any matrix, understand their significance in transformations, and apply them to solve complex linear systems.
Mathematik für Ingenieure 3
Umfassende Einführung in mehrdimensionale Integration und Vektoranalysis für Ingenieure, mit Fokus auf praktische Anwendungen und Problemlösungen in der höheren Mathematik.
Linear Algebra
Umfassende Einführung in die lineare Algebra mit Schwerpunkt auf Matrizen, Determinanten, Eigenwerte und komplexe Zahlen. Praktische Anwendungen und Übungen vertiefen das Verständnis.
Teoria Ergódica Diferenciável - Aula 17
Explore advanced concepts in Differentiable Ergodic Theory, including ergodic equivalence, partitions, spectral equivalence, and mixing in this doctoral-level mathematics lecture.