Consuming O16N Web Services from Azure Functions

Operationalization feature of Microsoft Machine Learning Server allows us to publish R/Python models and code in the form of web services and the consume these services within client applications. This article outlines step-by-step details of consuming the published web service (R language) using Azure Functions (C# TimerTrigger). Azure Functions is a solution for easily running…


Importing data with Microsoft R Server

In this blog, we would play around a new package RevoScaleR which takes a different approach in handling the data. Though, it works directly with flat files, but, is primarily made for a special kind of file format: XDF which enhances processing of the datasets. RevoScaleR package stores the dataset on disk (hard drive) and…

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Encrypting Communication between Web Node and Compute Node in Linux

This article walks you through the steps for encrypting the traffic between web nodes and compute nodes in Linux using self-signed certificates. If a compute node is inside the web node’s trust boundary, then encryption of this piece isn’t needed. However, if the compute node resides outside of the trust boundary, consider using the compute…


Using R to generate API Client from Swagger

Microsoft R Server’s operationalization feature enables data scientists to deploy and consume web services to operationalize their R analytics. The publishService() function in mrsdeploy package can be used to publish an R code block as a new web service. After it has been deployed, the web service can be: Consumed directly in R by another…


From DeployR to R Server Operationalization

If you are currently using DeployR (DeployR Enterprise 7.4 or R Server 8.0.x DeployR), this article will help you understand: The differences between DeployR and R Server 9 Operationalization How to upgrade to R Server 9 Operationalization The differences between DeployR and R Server 9.x Operationalization In R Server 9.0, Microsoft introduced a set of…

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Role Based Access Control With MRS 9.1.0

In the latest release of Microsoft R Server 9.1 we can configure role based access control (RBAC) for users who can publish, modify and delete the web services. There are three roles in MRS 9.1 and each role has defined set of permissions for what they can do and what they cannot do. Owner: users…


Galaxy classification with neural networks: a data science workflow

Recently at the Microsoft Ignite 2017 conference on the Gold Coast, I gave a talk about some cool new features we’ve introduced in Microsoft R Server 9 in the last 12 months: MicrosoftML, a powerful package for machine learning Easy deployment of models using SQL Server R Services Creating web service APIs with R Server Operationalisation (previously…


REST Calls using PostMan for R server Operationalization

The Microsoft R Server operationalization REST APIs are exposed by R Server’s operationalization server, a standards-based server technology capable of scaling to meet the needs of enterprise-grade deployments. With the operationalization feature configured, the full statistics, analytics and visualization capabilities of R can now be directly leveraged inside Web, desktop and mobile applications. Core Operationalization…


Reference implementation of credit risk prediction using R

This post is authored by Surendra Tipparaju and Durga Prasad Chappidi at Microsoft Credit risk prediction is one of most common models and yet most revisited. The risk assessment is determined based on dataset and number of features that can be included in the model. We have implemented the initial model few months back in…


Classify Yelp restaurant reviews’ food origin with MicrosoftML

Yelp restaurant reviews are one of the most useful resources people use to pick restaurants. Reviews themselves not only carry sentiment towards the dining experience but also contain “meta-information” about the restaurant. For example, looking at a review that says We can tell that this is a Japanese restaurant since it mentions omakase and sushi. Natural language processing and machine…