Data Science and Machine Learning (Theory and Projects) A to Z - Mathematical Foundation: Positive Semi Definite Matrix

The video tutorial introduces the concepts of eigenvalues, eigenvectors, and eigenspaces, emphasizing their significance in data science and optimization. It explains how eigenvectors maintain their direction when multiplied by a matrix and discusses the properties of eigenvalues and eigenvectors, including examples. The tutorial also covers the concept of eigenspace and its relation to eigenvectors and eigenvalues, and introduces complex eigenvalues and positive semidefinite matrices, which are crucial in optimization and data science models.

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