A common technique to reduce overfitting in neural networks is to apply ______________, which randomly drops units from the neural network during training.

A common technique to reduce overfitting in neural networks is to apply ______________, which randomly drops units from the neural network during training.

______________ is a technique used in training neural networks where multiple models are trained and combined to improve performance and robustness

In neural networks, ______________ normalization is applied to stabilize and speed up the training process.

Dropout is a technique used to prevent overfitting by randomly turning off a fraction of neurons during training.Group of answer choicesTrueFalse

Which of the following is not part of the ML training phase?Evaluating the modelsData managementCreate the modelsConnecting Neural Networks