Analyzing network weights and more

In the previous recipe, we focused on visualizing the loss and metric. However, with TensorBoard, you can also keep track of the weights. Taking a closer look at the weights can help in understanding how your model works and learns. 

How to do it...

1. We start by importing TensorFlow, as follows:

import tensorflow as tf
from tensorflow.examples.tutorials.mnist import input_data

2. Now, we will be able to load the Fashion-MNIST dataset with just one line of code:

mnist = input_data.read_data_sets('Data/fashion', one_hot=True)

3. Before proceeding, we need to set the placeholders for our model:

n_classes = 10
input_size = 784

x = tf.placeholder(tf.float32, shape=[None, input_size...