Matrix Methods
Learn the basics of Matrix Methods for machine learning and data analysis. Discover Singular Value Decomposition and Principal Component Analysis. Optional Python examples included.
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. Optional examples using Python are used to illustrate the concepts and allow the learner to experiment with the algorithms.
What you will learn
Matrices as Mathematical Objects
Matrix Multiplication and other Operations
Systems of Linear Equations
Linear Least Squares
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