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I noticed that the current visualization section in the Microsoft Data Science Beginner Course mentions relationships between features but does not explore how they can be analyzed quantitatively, such as using the Pearson correlation which is perfect way to analyze the relationship between features and how each feature correlated with other features including target feature. Incorporating Pearson correlation analysis can provide valuable insights into feature relationships, which are crucial for data preprocessing and feature engineering.
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