Which of the following is a way to prevent overfitting in a Keras model?

A)  Adding more layers
B)  Adding dropout layers
C)  Decreasing the batch size
D)  Increasing the learning rate

Correct Answer :   Adding dropout layers

Explanation : Dropout layers randomly drop out some of the neurons during training, which can help prevent overfitting.

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