Linear Algebra Series - Change of Basis Matrix Solver
Interactive Solver for the Change of Basis Matrix
Linear Algebra Series - The Four Fundamental Subspaces Solver
Interactive Solver for The Four Fundamental Subspaces - Column Space, Row Space, Null Space and the Left Null Space
Linear Algebra Series - Special Topics
We round out the course with advanced frontiers. From Jordan Canonical Forms for defective matrices to an introduction to Tensors, these topics bridge the gap between standard linear algebra and advanced theoretical physics or machine learning research.
Linear Algebra Series - Principal Component Analysis (PCA)
In the age of Big Data, we have too many variables. PCA uses linear algebra to reduce dataset dimensionality while keeping the most important information, simplifying complex data clusters into understandable, actionable patterns.
Linear Algebra Series - Singular Value Decomposition (SVD)
The pinnacle of linear algebra, SVD works on any matrix. We learn to break a matrix into strictly orthogonal components, a technique crucial for image compression, noise reduction, and modern recommendation systems.
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