Migrates using Image to using Environment in the o16n notebook

[Chris113113]

Description

Creating and deploying a ContainerImage is soon-to-be deprecated functionality inside of AzureML service.

The new recommended flow is instead to prepare an Environment object that contains your Pip/Conda requirements and simply include this in your InferenceConfiguration to be supplied in a Model.deploy() call.

This speeds up image build and service deployment time, and allows subsequent service deployments to leverage existing prepared Environment images.

Related Issues

#962

Checklist:

• I have followed the contribution guidelines and code style for this project.
• I have added tests covering my contributions. (Covered by existing tests)
• [?] I have updated the documentation accordingly. (I have updated in-line documentation in the notebook, not sure if there's other documentation that needs to be updated.

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[miguelgfierro]

I get an error when importing the environment dependencies:

from azureml.core import Environment
from azureml.core.environment import CondaDependencies
from azureml.core.model import InferenceConfig
from azureml.core.environment import SparkSection, SparkPackage

Right now we are using azureml-sdk[databricks]==1.0.8 https://github.com/microsoft/recommenders/blob/master/scripts/databricks_install.py#L237
should we change this to a newer version?

[miguelgfierro]

@Chris113113 I created a new branch called ignite, rebased to that branch and I will change the version of azureml there