The Data Science Virtual Machine (DSVM) is a ‘Windows Server 2016 with Containers’ VM & includes popular tools for data exploration, analysis, modeling & development.
Highlights:
- Azure Machine Learning
- Azure Data Factory
- Stream Analytics
- SQL Data Warehouse
- Hadoop + Apache Spark (HDICluster)
- Data Lake
- Blob storage
- ML & Data Science tutorials as Jupyter notebooks
Tools for ML model operationalization as web services in the cloud, using Azure ML or Microsoft R Server.
Pre-configured and tested with Nvidia drivers, CUDA Toolkit, & NVIDIA cuDNN library for GPU workloads available if using NC class VM SKUs.
Starting in the Azure Portal
GO to New or +
Search for Data Science Virtual Machine (DSVM)
Select the {csp} Data Science Virtual Machine – Windows 2016 option.
Next fill in the username and password with resource group.
Pick a machine type. When you pick a higher machine type when deploying every thing is way faster than just picking a Standard_A1 size.
As you can see there is a orange mark in the text that the cost will be billed separately.
Offer details
Data Science Virtual Machine – Windows 2016
0.0000 EUR/hr
Good to know there are no cost and this is free. you need to pay for the Azure VM! in my case a E32s v3
The highlighted Marketplace purchase(s) are not covered by your Azure credits, and will be billed separately.
You cannot use your Azure monetary commitment funds or subscription credits for these purchases. You will be billed separately for marketplace purchases.
not bad 9 minute install with a long list of tools Office, visual studio , Visual studio Code,etc
There is not a free license for the office and studio product but you can sign in with your credentials.
Thanks to the Big compute everything is running awesome.
As you can see all the tools are there, some needs a configuration so no default things that needs to be removed first just ready to start with out the long installation of all the tools.
What was missing on the Data Science Virtual Machine (DSVM) as it is a DevOps VM I installed the RSAT tools and project Honolulu single box for Azure management and development.
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