Explain the importance of bias and variance related to overfitting and underfitting and How to address it using regularization?

Q1.2 Also try to see if the model performance can be improved with feature selection.
Q2. What is the difference between correlation and regression?
Q3. Give three situations when correlation implies causation.
Q4. Give three situation when correlation does not imply causation
Q5. Explain the importance of bias and variance related to overfitting and underfitting and How to address it using regularization?

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