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This script is best run interactively to review its operation and to
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ensure that the interaction with Azure completes.
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A common use case is for a Data Scientist to create their R programs
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to analyse a dataset on their local compute platform (e.g., a laptop
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with 6GB RAM running Ubuntu with R installed). Development is
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performed with a subset of the full dataset (a random sample) that
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will not exceed the available memory and will return results
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quickly. When the experimental setup is complete the script can be
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sent across to a considerably more capable compute engine on Azure,
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possibly a cluster of servers to build models in parallel.
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This tutorial will deploy several Linux Data Science Virtual Machines
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(DSVMs), distribute a copmute task over those servers, colelct the
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results and generate a report, and then delete the compute
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resources.
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# Setup
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To get started load our Azure credentials as well as the user's ssh
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