In this section, we will learn about the Modified National Institute of Standards and Technology (MNIST) database data and build a simple classification model. The objective of this section is to learn the general framework for deep learning and use TensorFlow for the same. First, we will build a perceptron or logistic regression model. Then, we will train a CNN to achieve better accuracy. We will also see how TensorBoard helps visualize the training process and understand the parameters.
The MNIST data has handwritten digits from 0–9 with 60,000 images for training and 10,000 images for testing. This database is widely used to try algorithms with minimum preprocessing. It's a good and compact database to learn machine learning algorithms. This is the most famous database for image classification problems. A few examples are shown here:
As can be seen in the preceding figure, there are 10 labels for these handwritten characters. The...
