Hands-On Deep Learning for Images with TensorFlow

Machine learning REST service

Now that we've got our Docker file built and readable, we're going to run a REST service inside of our container. In this section, we will take a look at running Docker and the correct command-line arguments, the exposed URL from our REST service, and then finally we'll be verifying that Keras is fully installed and operational.

And now for the payoff: we're actually going to run our container using the docker run command. There's a couple of switches we're going to pass here. -p is going to tell us that port 8888 on the container is port 8888 on our PC, and the -v command (and we're actually going to mount our local work directory, which is where we cloned the source code from GitHub) will be mounted into the ...