Mathematical Matrix Methods lie at the root of most methods of machine learning and data analysis of tabular data. Learn the basics of Matrix Methods, including matrix-matrix multiplication, solving linear equations, orthogonality, and best least squares approximation. Discover the Singular Value Decomposition that plays a fundamental role in dimensionality reduction, Principal Component Analysis, and noise reduction.
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Optional examples using Python are used to illustrate the concepts and allow the learner to experiment with the algorithms.
Course Syllabus
Week 1 - Matrices as Mathematical Objects
Week 2 - Matrix Multiplication and other Operations
Week 3 - Systems of Linear Equations
Week 4 - Linear Least Squares
Week 5 - Singular Value Decomposition