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moe18 merged 1 commit into from
Sep 3, 2025
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Update learn.md problem 37 #524

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4 changes: 2 additions & 2 deletions questions/37_calculate-correlation-matrix/learn.md
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Expand Up @@ -10,8 +10,8 @@ $$
$$

#### Where:
- \( \text{cov}(X, Y) \) is the covariance between \( X \) and \( Y \).
- \( \sigma_X \) and \( \sigma_Y \) are the standard deviations of \( X \) and \( Y \), respectively.
- $$ \text{cov}(X, Y) $$ is the covariance between \( X \) and \( Y \).
- $$ \sigma_X $$ and $$ \sigma_Y $$ are the standard deviations of \( X \) and \( Y \), respectively.

### Problem Overview
In this problem, you will write a function to calculate the correlation matrix for a given dataset. The function will take in a 2D numpy array \( X \) and an optional 2D numpy array \( Y \). If \( Y \) is not provided, the function will calculate the correlation matrix of \( X \) with itself.
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