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Merge pull request MicrosoftDocs#1473 from jeannt/newpy
Bug fixes and TOC updates
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‎docs/advanced-analytics/TOC.md‎

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<!-- ### [Resource Governance for Python](python/resource-governance-for-python.md)-->
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# [Machine Learning Server (Standalone)](r/r-server-standalone.md)
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# [Machine Learning Server - Standalone](r/r-server-standalone.md)
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## [Getting Started](r/getting-started-with-microsoft-r-server-standalone.md)
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## [Set up Machine Learning Server Standalone](r/create-a-standalone-r-server.md)
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### [Install Microsoft Machine Learning Server from the Command Line](r/install-microsoft-r-server-from-the-command-line.md)
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### [Set up Data Science Tools](r/setup-or-configure-r-tools.md)
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### [Set Up a Data Science Client](r/set-up-a-data-science-client.md)
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## [Blog](https://blogs.technet.microsoft.com/machinelearning/)
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## [Feedback Forum](https://social.msdn.microsoft.com/Forums/sqlserver/home?category=sqlserver)
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## Blogs
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### [SQL Server](https://blogs.technet.microsoft.com/dataplatforminsider/)
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### [R Server](https://blogs.msdn.microsoft.com/microsoftrservertigerteam/)
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### [Machine Learning](https://blogs.technet.microsoft.com/machinelearning/)
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## Feedback Forums
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### [SQL Server](https://social.msdn.microsoft.com/Forums/sqlserver/home?category=sqlserver)
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### [Microsoft R Server](https://social.msdn.microsoft.com/Forums/azure/home?forum=MicrosoftR)
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# [Reference](r/machine-learning-services-r-reference.md)
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## [MicrosoftML](using-the-microsoftml-package.md)
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## [RevoScaleR](r/revoscaler-overview.md)
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### [ScaleR Functions for Working with SQL Server Data](r/scaler-functions-for-working-with-sql-server-data.md)
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### [ScaleR Functions for SQL Server Data](r/scaler-functions-for-working-with-sql-server-data.md)
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## [SqlRUtils](r/generating-an-r-stored-procedure-for-r-code-using-the-sqlrutils-package.md)
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## [OlapR](r/how-to-create-mdx-queries-using-olapr.md)
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## [What is RevoScalePy](python/what-is-revoscalepy.md)
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## [RevoScalePy](python/what-is-revoscalepy.md)
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# [Machine Learning Tutorials](tutorials/machine-learning-services-tutorials.md)
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# [Tutorials](tutorials/machine-learning-services-tutorials.md)
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## [Run Python using T-SQL](tutorials/run-python-using-t-sql.md)
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## [Create a Model using revoscalepy](tutorials/use-python-revoscalepy-to-create-model.md)
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## [Deploy and Consume Python Models](../advanced-analytics/python/publish-consume-python-code.md)
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## [Using R Code in Transact-SQL (Basic Tutorial)](tutorials/rtsql-using-r-code-in-transact-sql-quickstart.md)
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### [Working with Inputs and Outputs (R in T-SQL Tutorial)](tutorials/rtsql-working-with-inputs-and-outputs.md)
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### [R and SQL Data Types and Data Objects (R in T-SQL Tutorial)](tutorials/rtsql-r-and-sql-data-types-and-data-objects.md)
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### [Using R Functions with SQL Server Data (R in T-SQL Tutorial)](tutorials/rtsql-using-r-functions-with-sql-server-data.md)
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### [Create a Predictive Model (R in T-SQL Tutorial)](tutorials/rtsql-create-a-predictive-model-r.md)
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### [Predict and Plot from Model (R in T-SQL Tutorial)](tutorials/rtsql-predict-and-plot-from-model.md)
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## [Python: Run Python using T-SQL](tutorials/run-python-using-t-sql.md)
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## [Python: Create a Model using revoscalepy](tutorials/use-python-revoscalepy-to-create-model.md)
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## [Python: Deploy and Consume Models](../advanced-analytics/python/publish-consume-python-code.md)
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## [Data Science End-to-End Walkthrough](tutorials/walkthrough-data-science-end-to-end-walkthrough.md)
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## [R: Use R Code in Transact-SQL](tutorials/rtsql-using-r-code-in-transact-sql-quickstart.md)
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### [Working with Inputs and Outputs](tutorials/rtsql-working-with-inputs-and-outputs.md)
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### [R and SQL Data Types and Data Objects](tutorials/rtsql-r-and-sql-data-types-and-data-objects.md)
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### [Using R Functions with SQL Server Data](tutorials/rtsql-using-r-functions-with-sql-server-data.md)
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### [Create a Predictive Model](tutorials/rtsql-create-a-predictive-model-r.md)
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### [Predict and Plot from Model](tutorials/rtsql-predict-and-plot-from-model.md)
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## [R: Data Science End to End Solution](tutorials/walkthrough-data-science-end-to-end-walkthrough.md)
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### [Prerequisites for Data Science Walkthroughs](tutorials/walkthrough-prerequisites-for-data-science-walkthroughs.md)
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### [Prepare the Data](tutorials/walkthrough-prepare-the-data.md)
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### [View and Explore the Data](tutorials/walkthrough-view-and-explore-the-data.md)
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#### [View and Summarize Data using R](tutorials/walkthrough-view-and-summarize-data-using-r.md)
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#### [Create Graphs and Plots Using R](tutorials/walkthrough-create-graphs-and-plots-using-r.md)
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### [Create Data Features](tutorials/walkthrough-create-data-features.md)
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### [Explore the Data](tutorials/walkthrough-view-and-explore-the-data.md)
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### [Summarize Data using R](tutorials/walkthrough-view-and-summarize-data-using-r.md)
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### [Create Graphs and Plots Using R](tutorials/walkthrough-create-graphs-and-plots-using-r.md)
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### [Create Data Features using SQL and R](tutorials/walkthrough-create-data-features.md)
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### [Build and Save the Model](tutorials/walkthrough-build-and-save-the-model.md)
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### [Deploy and Use the Model](tutorials/walkthrough-deploy-and-use-the-model.md)
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## [Data Science Deep Dive: Using the RevoScaleR Packages](tutorials/deepdive-data-science-deep-dive-using-the-revoscaler-packages.md)
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### [Lesson 1: Work with SQL Server Data using R](tutorials/deepdive-work-with-sql-server-data-using-r.md)
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## [R: Data Science Deep Dive with RevoScaleR](tutorials/deepdive-data-science-deep-dive-using-the-revoscaler-packages.md)
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### [Lesson 1: Work with SQL Server Data](tutorials/deepdive-work-with-sql-server-data-using-r.md)
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#### [Create SQL Server Data Objects using RxSqlServerData](tutorials/deepdive-create-sql-server-data-objects-using-rxsqlserverdata.md)
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#### [Query and Modify the SQL Server Data](tutorials/deepdive-query-and-modify-the-sql-server-data.md)
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#### [Define and Use Compute Contexts](tutorials/deepdive-define-and-use-compute-contexts.md)
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### [Lesson 5: Create a Simple Simulation](tutorials/deepdive-create-a-simple-simulation.md)
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## [In-Database Advanced Analytics for SQL Developers](tutorials/sqldev-in-database-advanced-analytics-for-sql-developers.md)
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## [R: In-Database Analytics for SQL Developers](tutorials/sqldev-in-database-advanced-analytics-for-sql-developers.md)
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### [Step 1: Download the Sample Data](tutorials/sqldev-download-the-sample-data.md)
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### [Step 2: Import Data to SQL Server using PowerShell](r/sqldev-import-data-to-sql-server-using-powershell.md)
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### [Step 3: Explore and Visualize the Data](tutorials/sqldev-explore-and-visualize-the-data.md)
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### [Step 4: Create Data Features using T-SQL](tutorials/sqldev-create-data-features-using-t-sql.md)
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### [Step 5: Train and Save a Model using T-SQL](r/sqldev-train-and-save-a-model-using-t-sql.md)
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### [Step 6: Operationalize the Model](tutorials/sqldev-operationalize-the-model.md)
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## [Data Science Scenarios and Solution Templates](tutorials/data-science-scenarios-and-solution-templates.md)
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# Samples
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## [Data Science Solution Templates](tutorials/data-science-scenarios-and-solution-templates.md)
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## [SQL Server Samples](https://github.com/Microsoft/sql-server-samples)
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## [Demand Forecasting with R Services](https://www.microsoft.com/sql-server/developer-get-started/r)
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## [Customer Clustering with R](https://www.microsoft.com/sql-server/developer-get-started/rclustering)

‎docs/advanced-analytics/python/what-is-revoscalepy.md‎

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---
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title: "What is revoscalepy | Microsoft Docs"
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title: "Introducing revoscalepy | Microsoft Docs"
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ms.custom: ""
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ms.date: "04/16/2017"
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ms.date: "04/27/2017"
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# What is revoscalepy
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# Introducing revoscalepy
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**revoscalepy** is a new library provided by Microsoft to support distributed computing, remote compute contexts, and high-performance algorithms for Python.
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> Python support is a new feature in SQL Server 2017 and is supported for preview only.
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> The **revoscalepy** module contains only a subset of the functionality provided in the corresponding **RevoScaler** package for R.
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> The **revoscalepy** module contains only a subset of the functionality provided in the corresponding **RevoScaleR** package for R.
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You can get data from any ODBC database, SQL Server, or XDF file, using the data soure functions listed in the following table.
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Remote compute contexts supported for this release are local, or in SQL Server 2017.
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### Functions
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The following functions are included in SQL Server 2017 CTP 2.0.
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| Function name | Category|
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| Function name | Category|
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> [!NOTE]
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> Open source distributions of Python do not support SQL Server compute contexts. However, you can install Microsoft Machine Learning Server to publish and consume Python applications from Windows without installing SQL Server. For more information, see [Create a Standalone R Server](../r/create-a-standalone-r-server.md)
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