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  • Blog Post: Azure Data Factory Now Integrates with Azure ML!

    An update to Azure Data Factory (ADF) now integrates this service with Azure Machine Learning, allowing you to run finished Azure ML models from within ADF pipelines. Click on this link or the image below for more details on how to take advantage of this feature. You can also visit the Azure Data...
  • Blog Post: Machine Learning – Hype or Reality? Microsoft ML Experts Weigh In

    The recent Practice of Machine Learning Conference at Microsoft concluded with a lively panel discussion moderated by principal researcher Misha Bilenko on the topic of: "Are We at Peak ML, or at the Start of AI Takeover? Hype vs. Reality of Machine Learning.” Our panelists were: ...
  • Blog Post: Weekend reading - 3 recent stories

    Three new stories about Microsoft ML and Advanced Analytics. 1. Fueling the Oil and Gas industry with IoT The oil and gas industry’s supply chain starts in some of world’s most remote areas and serves consumers globally in all the places where the finished product gets consumed....
  • Blog Post: Python Tools for Visual Studio now integrates with Azure Machine Learning

    This blog post is authored by Shahrokh Mortazavi , Partner Director of Program Management on the Microsoft Azure Machine Learning team. Two languages are closely associated with Data Science today – R and Python. In Azure ML we’ve supported R for some time – and very soon we’ll...
  • Blog Post: Microsoft ML featured on CIO magazine, WIRED, KDnuggets and PCWorld in the past week

    Microsoft’s Machine Learning technology got a bit of press coverage in the past week – here’s a quick round up of the major stories: 1. Internet of Things Helps Asthma Patients Breathe Easily Medical device company Aerocrine is reducing device downtime and better servicing hospitals...
  • Blog Post: AzureML Web Service Parameters

    Overview AzureML Web Service APIs are published from Experiments that are built using modules with configurable parameters. There is often a need to change the module behavior during Web Service execution. The Web Service Parameters feature enables this functionality. A common example is setting...
  • Blog Post: From Data to Operationalized ML in 60 Minutes!

    This blog post was co-authored by Debi Mishra , Jacob Spoelstra and Dmitry Pechyony of the Information Management & Machine Learning team at Microsoft. Microsoft has a strong track record for crafting tools such as our Office apps or Visual Studio which millions of users find relatively easy to...
  • Blog Post: Free webinar: Operationalizing R as a Web Service

    R is the most widely used language today for machine learning, but its power is sometimes limited by gaps in the technology meant to bring it to life. In this webinar, learn how you can use your existing skills in R in new ways, including deploying models as web services with a few clicks. The first...
  • Blog Post: How We Share Machine Learning Knowledge at Microsoft

    We recently concluded the Fall 2014 edition of our Practice of Machine Learning Conference (PMLC). Over 1,700 Microsoft employees attended the two day event, which featured 60 talks on a broad spectrum of areas ranging from new algorithms to ML applications such as anomaly detection and fraud. Tutorials...
  • Blog Post: Microsoft Research Grants Available for Azure, Including Machine Learning

    This article is a re-post from the Microsoft Research Connections Blog. A year ago, the Microsoft Azure for Research project began as a small effort to help external researchers and scientists (and Microsoft) understand how the cloud could accelerate research insights. The project enables researchers...
  • Blog Post: Information Week: Dell Bolsters Analytics Software, Taps Microsoft Azure ML

    Re-post of an article that ran earlier this week, from Information Week. Dell extends its big data analysis capabilities, adding natural-language processing and integrating Microsoft Azure Machine Learning services.
  • Blog Post: Microsoft adds free tier to Azure Machine Learning

    Starting today, we made it easier than ever for anyone to try Azure Machine Learning. Our service is now available to test free of charge without a subscription or credit card – all you need to get going is a Microsoft account! You can read more about this announcement, made at the PASS Summit...
  • Blog Post: Anomaly Detection – Using Machine Learning to Detect Abnormalities in Time Series Data

    This post was co-authored by Vijay K Narayanan , Partner Director of Software Engineering at the Azure Machine Learning team at Microsoft. Introduction Anomaly Detection is the problem of finding patterns in data that do not conform to a model of “normal” behavior. Detecting such deviations...
  • Blog Post: The Ins and Outs of Azure Stream Analytics – Real-Time Event Processing

    Earlier this week, at TechEd Europe 2014 in Barcelona, we announced the preview of Azure Stream Analytics . Azure Stream Analytics is a cost-effective event processing engine that helps uncover real-time insights from devices, sensors, infrastructure, applications and data quickly and easily. Learn...
  • Blog Post: The Ins and Outs of Azure Data Factory – Orchestration and Management of Diverse Data

    Earlier this week, at TechEd Europe 2014 in Barcelona, we announced the preview of Azure Data Factory . Azure Data Factory enables information production by orchestrating and managing diverse data. Learn about the ins and outs of this new service here . ML Blog Team
  • Blog Post: Embracing Uncertainty – Probabilistic Inference

    This is the second of a 2-part blog post by Chris Bishop , Distinguished Scientist at Microsoft Research. The first part is available here . Last week we explored the key role played by probabilities in machine learning, and we saw some of the advantages of arranging for the outputs of a classifier...
  • Blog Post: Microsoft Adds Streaming Analytics, Data Production and Workflow Services to Azure

    This is a repost of an article by Joseph Sirosh on Microsoft’s Data Platform Insider blog in which we announced three new services earlier today: Azure Stream Analytics , a cost-effective event processing engine that helps uncover real-time insights from devices, sensors, infrastructure...
  • Blog Post: Embracing Uncertainty – the Role of Probabilities

    This is the first of a 2-part blog post by Chris Bishop , Distinguished Scientist at Microsoft Research. The second part was later posted here . Almost every application of machine learning (ML) involves uncertainty. For example, if we are classifying images according to the objects they contain,...
  • Blog Post: From Stumps to Trees to Forests

    This blog post is authored by Chris Burges , Principal Research Manager at Microsoft Research, Redmond. In my last post we looked at how machine learning (ML) provides us with adaptive learning systems that can solve a wide variety of industrial strength problems, using Web search as a case study...
  • Blog Post: Video - Joseph Sirosh Interview with theCUBE at BigDataNYC 2014

    Joseph Sirosh was recently interviewed in NYC by Dave Vellante and Jeff Frick on theCube . He covers a lot of ground including suggestions for aspiring data scientists, the great opportunity on the Azure marketplace and also the future of machine learning and Azure ML Check out the video below. ...
  • Blog Post: Video - Joseph Sirosh Keynote: "A New Data Science Economy" at Strata + Hadoop 2014

    Be sure to check out Joseph's keynote talk below, under 10 minutes long, summarizing how, in the emerging new Data Science Economy, data scientists are able to monetize their skills - at scale, in the cloud - just like app developers have been able to do for several years now. Joseph blogged about...
  • Blog Post: Web Services and Marketplaces Create a New Data Science Economy

    This blog post is authored by Joseph Sirosh , Corporate Vice President of Machine Learning at Microsoft. Yesterday, at Strata + Hadoop World , we announced the expansion of our data services with support of real-time analytics for Apache Hadoop in Azure HDInsight and new machine learning (ML) capabilities...
  • Blog Post: Distributed Cloud-Based Machine Learning

    This post is authored by Dhruv Mahajan , Sundararajan Sellamanickam and Keerthi Selvaraj , Researchers at Microsoft’s Cloud & Information Services Lab (CISL) and at Microsoft Research. Enterprises of all stripes are amassing huge troves of data assets, e.g. logs pertaining to user behavior...
  • Blog Post: Azure ML is Helping CMU Become More Energy Efficient

    Posted by Vinod Anantharaman , head of business strategy, Microsoft Information Management and Machine Learning (IMML). Buildings are powered by multiple systems such as heating, cooling, lighting, ventilation, security and more, each of which affect occupant comfort and energy consumption. Traditionally...
  • Blog Post: Vowpal Wabbit Modules in AzureML

    This post is authored by Sudarshan Raghunathan , Principal Development Lead for modules in the Microsoft Azure ML Studio team based in Cambridge, MA. In his blog post last month, John Langford wrote about the open source Vowpal Wabbit (VW) machine learning (ML) system. He highlighted some of the...