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Lec-46: Principal Component Analysis (PCA) Explained | Machine Learning

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Lec-46: Principal Component Analysis (PCA) Explained | Machine Learning

In this video, we explain how Principal Component Analysis (PCA) works and how it's used for dimensionality reduction. Learn how PCA identifies the principal components of your data by calculating eigenvalues and eigenvectors, and how these components capture the most important features of the dataset

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Principal Component Analysis (PCA) Explained | Dimensionality Reduction in Machine Learning

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