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4 Modules
Which of the following statements about activation functions in neural networks is true?
Activation functions introduce non-linearity into the model.
ReLU can suffer from the vanishing gradient problem.
Sigmoid activation functions are preferred for hidden layers in deep networks.
Softmax is typically used in the output layer for multi-class classification.
In the context of Convolutional Neural Networks (CNNs), what is the purpose of pooling layers?
To reduce the spatial dimensions of the input volume.
To increase the number of parameters in the model.
To introduce non-linearity into the model.
To extract features from the input data.
Which of the following optimizers is known for adapting the learning rate during training?
SGD (Stochastic Gradient Descent)
Adam
RMSprop
Adagrad
What is the main advantage of using LSTM (Long Short-Term Memory) networks over traditional RNNs (Recurrent Neural Networks)?
LSTMs can remember information for long periods.
LSTMs are simpler to implement than RNNs.
LSTMs do not suffer from the vanishing gradient problem.
LSTMs can process data in parallel.
Which of the following techniques can help prevent overfitting in neural networks?
Dropout
Batch normalization
Increasing the number of epochs
Data augmentation
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4 Modules