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What is Linear Regression?

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Linear regression is a machine learning method to predict numbers (like prices or scores). It fits a straight line to data to show the relationship between input (features) and output (target).

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Advantages ⭐️

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1. Works well with linearly separable data.
2. Easy to implement and train.
3. Handles overfitting with techniques like cross-validation, and regularization.

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Disadvantages ⭐️

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1. Sometimes Lot of Feature Engineering Is required
2. If the independent features are correlated it may affect performance
3. Sensitive to noise

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Whether Feature Scaling is required? ⭐️

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Yes