In this section, we're going to add another convolutional layer to our model. Don't worry, we'll walk through the parameters to make sizing line up and we'll learn what dropout training is.
As usual, when starting a new model, make a fresh IPython session and execute the code up to num_filters1. Great, now you're all set to start learning. Let's jump into our convolutional model.
Why don't we be ambitious and set the first convolutional layer to have 16 filters, far more than the 4 from our old model. But, we'll use a smaller window size this time. Just 3x3. Also note that we changed some variable names such as num_filters to num_filters1. This is because we're going to have another convolutional layer in just a moment and we might want a different number of filters on each. The rest of this layer is exactly as it was before, we can convolve and do 2x2 max pooling and we use the rectified linear activation unit.
Now we add another convolutional...