Professor Strang's Related Courses on OCW
A new version of this classic Linear Algebra course was released in 2011 in the innovative OCW Scholar format designed for independent learners. 18.06SC Linear Algebra includes 35 lecture videos and 36 short (and highly-praised) problem-solving help videos by teaching assistants.
Professor Strang has continued to offer new insights into key mathematics subjects. In 2014, he published the new textbook Differential Equations and Linear Algebra. In 2016, that textbook was developed into a series of 55 short videos supported by MathWorks, with parallel videos about numerical solutions by Dr. Cleve Moler, the creator of MATLAB®. The textbook and video lectures help students in a basic ordinary differential equations course. This new series, Learn Differential Equations: Up Close with Gilbert Strang and Cleve Moler, is also available on the MathWorks website.
In 2017, Professor Strang launched a new undergraduate course at MIT: 18.065 Matrix Methods in Data Analysis, Signal Processing, and Machine Learning. Published on the OCW site in 2019, the course uses linear algebra concepts for understanding and creating machine learning algorithms, especially as applied to deep learning and neural networks. This course reviews linear algebra with applications to probability and statistics and optimization and, above all, a full explanation of deep learning.
Professor Strang's latest course on the topic is A 2020 Vision of Linear Algebra. These six brief videos contain ideas and suggestions from Professor Strang about the recommended order of topics in teaching and learning linear algebra. The first topic is called A New Way to Start Linear Algebra. That leads to The Column Space of a Matrix. The remaining videos outline very briefly the full course: The Big Picture of Linear Algebra; Orthogonal Vectors; Eigenvalues & Eigenvectors; and Singular Values & Singular Vectors.
The Java® Demos were developed by Pavel Grinfeld.
- SVD (Singular Value Decomposition)
- Gaussian Elimination
- Gram-Schmidt = Orthogonalization
- Inner Product of Functions
- Sum of Fourier Series
- Sum of Trigonometric Series
- Gibbs Phenomenon
- Column Spaces
- Least Squares
- Power Method
- Gauss-Jordan Demo
- LU Demo
- The Media Lab's Eigenfaces Demo
- Projections of Famous and not so Famous Three and Four Dimensional Solids
- Best Guide to MATLAB® (PDF)
- Short MATLAB® Tutorial (PDF) and Cool MATLAB® demos by Mathworks
- MATLAB® Recitation Demos from 1997
- MATLAB® Teaching Codes
- A MATLAB cheat sheet (PDF)
- Pascal Matrices (PDF)
- A Basis for 3 by 3 Symmetric Matrices (PDF)
- Gram-Schmidt in 9 Lines of MATLAB® (PDF)
- Linear Algebra and Music (PDF)
Essays on Teaching Linear Algebra
- Too Much Calculus (PDF)
- Starting with Two Matrices (PDF)
- The Four Fundamental Subspaces: 4 Lines (PDF)
- Fourier Sine Series Examples (PDF)
- Notes on function spaces, Hermitian operators, and Fourier series (PDF)