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 with minimum delay (chapter 11)
- Understand the theory of the MobileNet model, as this is often deployed in edge devices due to its speed...
