Answer Posted / Rakesh Kumar Saroj

Avoiding overfitting can be achieved through techniques such as regularization (adding a penalty term to the loss function to discourage large weights), early stopping (stopping training before the model starts memorizing the training data), cross-validation (using multiple subsets of the data for validation), and using simpler models or feature selection.

What are standardization and normalisation? Give one advantage of each over the other?

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