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Question: What is the concept of regularization in machine learning, and how does it prevent overfitting?
Answer: Regularization is a technique to prevent overfitting by adding a penalty term to the loss function based on the complexity of the model. Common regularization methods include L1 and L2 regularization, dropout, and early stopping.

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