In this section, we will see how to create a multilayer convolutional network in TensorFlow and watch how a deeper network improves classification accuracy. We will define the layers with TensorFlow layers' APIs rather than defining them from scratch. The best practice methods are engrained in those methods. The import of libraries, datasets, and placeholders can be followed from the previous section. This time, we will use TensorBoard for visualizing the training process. In order to visualize the statistics of the variables, the values of variable statistics have to be added to tf.summary.
The summaries will be written to a folder that is interpretable to TensorBoard. Let's define a function ...
