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Which of the following strategies can be used to reduce overfitting in machine learning models? Choose the best answer.
A
Data Augmentation (e.g., Image scaling, rotation to enhance training data diversity)
B
Dropout, a technique that randomly deactivates neurons during training to prevent overfitting
C
Early Stopping, halting training before the model starts overfitting
D
Regularization techniques like L1 and L2 to penalize large weights and simplify the model
E
All of the above
