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…

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Demonstration of capability of applying simple ML and TextMining techniques to perform prediction and draw allied characteristics

The Write-up is to demonstrate a simple ML algorithm that can pull-up the characteristic components of the data to predict the family to which  it belongs. In this particular example, the data set had a list of id, ingredients and dish. There were 20 types of dish in the data set. The data-scientist is attempting…


R Server and Shiny

This post is authored by Carl Nan, Principle Program Manager at Microsoft. With the release of Microsoft R Server (Version 9.0), Microsoft introduced a new set of capabilities to help enterprises deploy their R analytics into production environments. MRS 9.0 enabled R analytics to be exposed as web services so that they can be integrated…

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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…

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Microsoft R Server VMs available in Azure China

 This post is authored by Bharath Sankaranarayan, Principal Program Manager, at Microsoft. We have expanded our footprint of Microsoft R Server Virtual Machines and is available in Azure China, both China North and China East. This will provide our customers the ability to leverage Microsoft R Server 9.0 for building advanced analytics solutions in the…


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…

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Exporting large data using Microsoft R (IDE: RTVS)

Introduction Very often in our projects we encounter a need to export huge amount of data (in GBs) and the conventional solution, write.csv, can test anyone’s patience with the time it demands. In this blog, we will learn by doing. We make use of a package that is not very popular, but serves the purpose…

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Predicting Hospital Length of Stay (LOS) using SQL Server 2016 with R Services

This post is authored by Bharath Sankaranarayan, Principal Program Manager, at Microsoft. Today we are excited to announce a Hospital length of Stay solution, leveraging SQL Server 2016 with R Services.  This solution accelerator will enable hospitals and healthcare providers to leverage machine learning to improve the prediction on how long a patient is expected to stay….