Data Science Virtual Machine.
Virtual machine with tools for the data science modeling and development
The
Data Science Virtual Machine runs on Windows Server 2012 and contains
popular tools for data exploration, modeling and development activities.
The main tools included are Microsoft R Server Developer Edition (An
enterprise ready scalable R framework), Anaconda Python distribution,
Julia Pro developer edition, Jupyter notebooks for R, Python and Julia,
Visual Studio Community Edition with Python, R and node.js tools, Power
BI desktop, SQL Server 2016 Developer edition including support
In-Database analytics using Microsoft R Server. It also includes open
source deep learning tools like Microsoft Cognitive Toolkit (CNTK 2.0)
and mxnet; ML algorithms like xgboost, Vowpal Wabbit. The Azure SDK and
libraries on the VM allows you to build your applications using various
services in the cloud that are part of the Cortana Analytics Suite which
includes Azure Machine Learning, Azure data factory, Stream Analytics
and SQL Datawarehouse, Hadoop, Data Lake, Spark and more. You can deploy
models as web services in the cloud on Azure Machine Learning OR
deploy them either on the cloud or on-premises using the Microsoft R
Server operationalization.
