Which of the following is a way to increase the capacity of a Keras model?

Keras - Quiz(MCQ)

Removing layers

Increasing the learning rate

Decreasing the number of neurons in each layer

Increasing the number of neurons in each layer

Correct Answer : Increasing the number of neurons in each layer

Explanation : Increasing the number of neurons in each layer can increase the capacity of the model, allowing it to learn more complex patterns in the data.

Recently Updated in Keras Questions

Which of the following is a fully connected layer whose output is sent back to the input?

RNN layer

Pooling layer

SimpleRNN layer

Embedding layer

Correct Answer : SimpleRNN layer

Explanation : SimpleRNN layer is a fully connected layer whose output is sent back to the input.

When sequential.pop() method raises a TypeError?

When there is no layer within the model

When there is the single layer within the model

When there are more than 10 layers within the model

None of the above

Correct Answer : When there is the single layer within the model

Explanation : sequential.pop() method raises a TypeError When there is a single layer within the model.

What does sequential.pop() method do?

It helps in the removal of the last layer from the model.

It helps in the removal of any layer from the model.

It helps in the removal of the first layer from the model.

All of the above

Correct Answer : It helps in the removal of the last layer from the model.

Explanation : Sequential.pop() functions help in the removal of the last layer from the model.

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