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Applying regularization to a linear regression model in scikit-learn

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I've heard about regularization, but I'm not sure how to apply it to a linear regression model in scikit-learn. Could someone explain what regularization is and provide guidance on its application?

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Regularization is like having a guide that keeps our model in check. It prevents the model from making up too many intricate details that might be specific to the training data but don't generalize well to new, unseen data.

For application, check our tutorial on Linear Regression for its application in Sklearn. 

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