Pre-trained AlexNet model for MicrosoftML’s rxNeuralNet

The rxNeuralNet model in MicrosoftML package supports custom neural networks defined using the NET# language. We can use the NET# language to define a convolutional neural network. In this blog we will give a NET# definition string for the AlexNet model. The model is a direct conversion of the Caffe implementation. It’s worth noting that an R implementation of AlexNet is barely available at the time this…


Feature Engineering using R

Feature Engineering is paramount in building a good predictive model. It’s significant to obtain a deep understanding of the data that is being used for analysis. The characteristics of the selected features are definitive of a good training model. Why is Feature Engineering important? Too many features or redundant features could increase the run time complexity of…


Running MicrosoftML in SQL Server 2016

MicrosoftML is the new and exciting ML packages added to Microsoft R Server 9.0.1 which offers increased speed, performance and scalability, especially for scenarios like deep neural network with GPU acceleration and highly-dimensional categorical data. There has been some confusions on where to download MicrosoftML to get your hands on algorithms like rxFastLiner, rxFastTress and rxNeuralNet,…


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…


11 ways to deploy R Server on HDInsight Cluster

In this article, we will discuss 11 possible ways to deploy R Server on HDInsight Cluster. Some of these ways will help in automating the cluster creation (using scripts). Majority of them are related to deployment using Azure Resource Manager Templates. ARM Templates are very useful and can be deployed in several ways. Here are the…


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…


Using R to perform FileSystem Operations on Azure Data Lake Store

In this article, you will learn how to use WebHDFS REST APIs in R to perform filesystem operations on Azure Data Lake Store. We shall look into performing the following 6 filesystem operations on ADLS using httr package for REST calls : Create folders List folders Upload data Read data Rename a file Delete a…


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…


Getting started with GPU acceleration for MicrosoftML’s rxNeuralNet

MicrosoftML’s rxNeuralNet model supports GPU acceleration. To enable GPU acceleration, you need to do a few things:   Install and configure CUDA on your Windows machine. For the purpose of this setup and later performance comparison, this is the machine used in this blog. There is an excellent old blog on how to do this. However, it’s slightly out of date…


Image Segmentation Using MicrosoftML

In computer vision, the goal of image segmentation is to cluster pixels into salient image regions, i.e., regions corresponding to individual surfaces, objects or natural parts of objects. The goal of segmentation is simplify and/or change the representation of an image into something that is more meaningful and easier to analyze. More precisely, image segmentation is…