Unsupervised learning: Young-Eckart-Mirsky theorem and intro to PCA

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This lecture covers the Young-Eckart-Mirsky theorem, which is essential in unsupervised learning, and introduces Principal Component Analysis (PCA) as a method for dimensionality reduction and data visualization. The slides discuss the theorem, PCA concepts, and the application of PCA in various fields.

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