Which strategy should you use when retraining the model?

You have trained a deep neural network model on Google Cloud. The model has low loss on the training data, but is performing worse on the validation data. You want the model to be resilient to overfitting.

Which strategy should you use when retraining the model?
A . Apply a dropout parameter of 0 2, and decrease the learning rate by a factor of 10
B . Apply a L2 regularization parameter of 0.4, and decrease the learning rate by a factor of 10.
C . Run a hyperparameter tuning job on Al Platform to optimize for the L2 regularization and dropout parameters
D . Run a hyperparameter tuning job on Al Platform to optimize for the learning rate, and increase the number of neurons by a factor of 2.

Answer: B

Explanation:

Applying a L2 regularization parameter of 0.4 and decreasing the learning rate by a factor of 10 can help to reduce overfitting and make the model more resilient. Source: Google Cloud