Module assessment

1.

You are creating a deep neural network to train a classification model that predicts to which of three classes an observation belongs based on 10 numeric features. Which of the following statements is true of the network architecture?

The input layer should contain three nodes

The network should contain three hidden layers

The output layer should contain three nodes

2.

You are training a deep neural network. You configure the training process to use 50 epochs. What effect does this configuration have?

The entire training dataset is passed through the network 50 times

The training data is split into 50 subsets, and each subset is passed through the network

The first 50 rows of data are used to train the model, and the remaining rows are used to validate it

3.

You are creating a deep neural network. You increase the Learning Rate parameter. What effect does this setting have?

More records are included in each batch passed through the network

Larger adjustments are made to weight values during backpropagation

More hidden layers are added to the network

4.

You are creating a convolutional neural network. You want to reduce the size of the feature maps that are generated by a convolutional layer. What should you do?

Reduce the size of the filter kernel used in the convolutional layer

Increase the number of filters in the convolutional layer

Add a pooling layer after the convolutional layer

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