Mastering Computer Vision with TensorFlow 2.x

Section 4: TensorFlow Implementation at the Edge and on the Cloud

In this section, you will use all your knowledge of computer vision and CNN acquired so far to package, optimize, and deploy a model in edge devices to solve real-life computer vision problems. Training large datasets in local machines takes time, so you will learn how to package your data and upload to containers in the cloud and then initiate training. You'll also see how to overcome some common bugs to complete your training and generate models successfully.

By the end of this section, you will be able to do the following:

• Understand how edge devices use various hardware acceleration and software optimization techniques to make inferences based on a neural network model ...