A Guide to TF Layers: Building a Convolutional Neural Network TensorFlow

The TensorFlow layers module provides a high-level API that makes it easy to construct a neural network. It provides methods that facilitate the creation of dense (fully connected) layers and convolutional layers, adding activation functions, and applying dropout regularization. In this tutorial, you'll learn how to use layers to build a convolutional neural network model to recognize the handwritten digits in the MNIST data set. The MNIST dataset comprises 60,000 training examples and 10,000 test examples of the handwritten digits 0–9, formatted as 28x28-pixel monochrome images. Let's set up the skeleton for our TensorFlow program.