#10. Eigenvalues and Eigenvectors in Machine Learning using Python | Tutorial
The video discusses the intuition behind vectors, Eigenvalues and Eigenvectors in Machine Learning. Timeline (Python 3.7) 00:00 - Welcome 00:09 - Outline of video 00:46 - What is a vector? 01:41 - Vector transformation: Scaling 02:06 - Vector transformation: Rotation 02:19 - Vector transformation: Rotation and Scaling 02:36 - Vector transformation: Translation 02:50 - What is a Determinant? 04:56 - What is a Dot Product? 06:16 - What is Cross Product? 07:16 - Importance of Eigenvalues and Eigenvectors in Machine Learning 08:58 - Intuition of Eigenvectors in PCA (Principal Component Analysis) 10:30 - Algebra Calculate Eigenvalues and Eigenvectors 11:51 - Python Calculate Eigenvalues and Eigenvectors 12:29 - Open Jupyter Notebook 12:37 - Import libraries 13:31 - Create data matrix 14:33 - Center data at zero 14:53 - Plot centered data 15:15 - PCA to calculate Eigenvalues and Eigenvectors 16:28 - linalg.eig() to calculate Eigenvalues and Eigenvectors 17:53 - linalg.svd() to calculate Eigenvalues and Eigenvectors 18:43 - Plot Eigenvectors on scatter plot 21:20 - End
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