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How Do Eigenvalues Work In PCA? - The Friendly Statistician
2:38
YouTubeThe Friendly Statistician
How Do Eigenvalues Work In PCA? - The Friendly Statistician
How Do Eigenvalues Work In PCA? Have you ever wondered how data scientists simplify complex datasets to find the most important information? In this informative video, we'll explain how eigenvalues work in Principal Component Analysis (PCA). We'll start by defining what PCA is and why it's a powerful tool for data analysis. You'll learn how PCA ...
2 days ago
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#covariance
Covariance, Clearly Explained!!!
Covariance, Clearly Explained!!!
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L12.6 Covariance Properties
L12.6 Covariance Properties
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Linear algebra is essential in both quantitative finance and machine learning for several reasons: In Quant Finance: Portfolio Optimization: Linear algebra helps in modeling and optimizing financial portfolios using matrix operations and eigenvalues. It's used to determine the best combination of assets. Risk Management: It’s used in models like Value at Risk (VaR), where covariance matrices and principal component analysis (PCA) are crucial for understanding market risk. Options Pricing: Many o
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