In this chapter, we are going to use the theoretical knowledge we have learned in previous chapters to create a mobile application that will classify a specific species of flower. By utilizing use your mobile camera and pointing it at a flower, the application will analyze the image and make its best educated guess as to the species of that flower. This is where we put to work the understanding we have gained about the workings of a convolutional neural network (CNN). We will also learn a bit more about using TensorFlow as well as some tools such as TensorBoard. But before we dive in too deep, let’s talk about a few things first.

Throughout this chapter we use terms that may not be familiar to all, so let’s make sure we’re all on the same page as to what they mean.

In this chapter, we will cover the following topics:

• CoreML versus TensorFlow Lite
• What is MobileNet
• Datasets for image classification
• Creating your own image dataset
• Using TensorFlow to build the model
• Running TensorBoard