AML: Clarify what DockerConfiguration does in `train-on-amlcompute.ipynb`

@keijik @cody-dkdc @gregce

In [this notebook](https://github.com/Azure/MachineLearningNotebooks/blob/master/how-to-use-azureml/training/train-on-amlcompute/train-on-amlcompute.ipynb) we are setting a docker configuration, and later passing that to the `docker_runtime` parameter

```py
from azureml.core import Environment
from azureml.core.runconfig import DockerConfiguration
from azureml.core.conda_dependencies import CondaDependencies

myenv = Environment("myenv")
myenv.python.conda_dependencies = CondaDependencies.create(conda_packages=['scikit-learn', 'packaging'])
# Enable Docker
docker_config = DockerConfiguration(use_docker=True)

....
from azureml.core import ScriptRunConfig
src = ScriptRunConfig(source_directory=project_folder,
script='train.py',
compute_target=cpu_cluster,
environment=myenv,
docker_runtime_config=docker_config)

run = experiment.submit(config=src)
```

Since we are using conda dependencies and are not specifying a base image, what is Docker doing exactly then?

The example works just fine if we omit the `docker_config` completely. So what is this example trying to show? What is the difference between passing this config and not passing it in practice?