Ml2p

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* Add support for client and server error exception handling.
* Deprecate passing a channel name to dataset_folder and add a new data_channel_folder
method to allow data in other channels to be accessed.
* Add dataset create and list commands to ml2p CLI.
* Add --version to ml2p and ml2p-docker CLIs.
* Allow model and endpoint version numbers to be multiple digits.

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* Added validation of naming convention

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* Added Sphinx requirements to build file.

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* Cleaned up support for passing ML2P environment data into training jobs and
model deployments. Environment settings such as the S3 URL and the project name
are now passed into training jobs via hyperparameters and into model deployments
via model environment variables.
* Added support for training and serving multiple models using the same docker
image by optionally passing the model to use into training jobs and endpoint
deployments.
* Added support for rich hyperparameters. This sidesteps SageMaker API's limited
hyperparameter support (it only supports string values) by encoding any
JSON-compatible Python dictionary to a flattened formed and then decoding
it when it is read by the training job.
* Added skeleton for Sphinx documentation.
* Removed old pre-0.0.1 example files.

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* Disabled direct internet access from notebooks by default.
* Added tests for cli_utils.

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* Fixed bug in setting of ML2P_S3_URL on model creation.