Data Science and Machine Learning (Theory and Projects) A to Z - Mathematical Foundation: Lagrange Multipliers

The video tutorial covers Singular Value Decomposition (SVD), explaining its independence from Principal Component Analysis (PCA). It defines orthogonal matrices and their properties, and details the process of decomposing a matrix using SVD. The tutorial provides a proof of SVD, explaining how to find matrices U, D, and V, and discusses the applications of SVD in data science.

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