In chapters 1-6 of this book, we have learned how to install and use Caffe2 to train DL neural networks and how to work with other popular DL frameworks. We have also learnt how to deploy our trained Caffe2 models on popular inference engines. In this last chapter, we will look at applications of Caffe2 that exploit its ability to scale from tiny edge devices such as the Raspberry Pi to running on containers in the cloud. We will also look at visualizing Caffe2 models.
The topics that will be covered in this chapter are as follows:
- Caffe2 at the edge on Raspberry Pi
- Caffe2 in the cloud using containers
- Caffe2 model visualization
