Dimensionality Reduction | ML-005 Lecture 14 | Stanford University | Andrew Ng
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Dimensionality Reduction | ML-005 Lecture 14 | Stanford University | Andrew Ng
Contents: Motivation 1 - Data Compression, Motivation 2 - Visualization, Principal Component Analysis - Problem Formulation, Principal Component Analysis Algorithm, Choosing the number of Principal Components, Reconstruction from Compressed Representation, Advice for Applying PCA.
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