Practical Convolutional Neural Networks

Building a single-layer neural network with TensorFlow

Let us build a single-layer neural net with TensorFlow step by step. In this example, we'll be using the MNIST dataset. This dataset is a set of 28 x 28 pixel grayscale images of hand written digits. This dataset consists of 55,000 training data, 10,000 test data, and 5,000 validation data. Every MNIST data point has two parts: an image of a handwritten digit and a corresponding label. The following code block loads data. one_hot=True means that the labels are one-hot encoded vectors instead of actual digits of the label. For example, if the label is 2, you will see [0,0,1,0,0,0,0,0,0,0]. This allows us to directly use it in the output layer of the network:

from tensorflow.examples.tutorials.mnist ...