Microsoft ML on Spark and Hadoop

MicrosoftML is a new package for Microsoft R Server that adds state-of-the-art algorithms and data transforms to Microsoft R Server functionality. The MicrosoftML package was available in Microsoft R Server for Windows and in SQL Server vNext. Now we bring the power of these algorithms to Spark and Hadoop. Training on a Hadoop/Spark cluster occurs in a…


What’s new in R Server 9.1 Operationalization

In Dec 2016, Microsoft R Server 9.0 introduced a new set of capabilities to help enterprises deploy their R analytics into production environments. In the latest release of R Server 9.1, Microsoft further improves on operationalization capabilities. This article will give a glance on those new exciting capabilities in R Server 9.1. Boost up the…

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Sentiment Analysis with a pre-trained model

Harnessing decades of work on cognitive computing in the context of Bing, Office 365 and Xbox, we are delivering the first installment of pre-trained cognitive models that accelerate time to value in Microsoft R Server 9.1. We now offer a Sentiment Analysis pre-trained cognitive model, using which you can assess the sentiment of an English sentence/paragraph with…

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Microsoft R Server support for Rattle

Rattle – the R Analytical Tool To Learn Easily – is a popular GUI for data mining using R. It presents intuitive graphical interface for data mining and analysis without actually writing the code.  It presents statistical and visual summaries of data, transforms data that can be readily modeled, builds both unsupervised and supervised models…

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Running Pleasingly Parallel workloads using rxExecBy on Spark, SQL, Local and Localpar compute contexts

RevoScaleR function rxExec(), allows you to run arbitrary R functions in a distributed fashion, using available nodes (computers) or available cores (the maximum of which is the sum over all available nodes of the processing cores on each node). The rxExec approach exemplifies the traditional high-performance computing approach: when using rxExec, you largely control how…


Image featurization with a pre-trained deep neural network model

With the new release of SQL Server vNext CTP 2.0 and Microsoft R Server 9.1, the MicrosoftML package has added support for pre-trained deep neural network models for image featurization. We can now use the following four deep neural network models in the featurizeImage machine learning transform to extract features from images. ResNet-18 ResNet-50 ResNet-101 AlexNet These four state-of-the-art deep…

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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…