Hello 2018 | Recap of “Top 10” Posts of 2017

As we ring in the new year, we’d like to kick things off in our usual fashion – with a quick recap of our most popular posts from the year just concluded. So here are our “Top 10” posts from 2017, sorted in increasing order of readership – enjoy! 10. Quick-Start Guide to the Data Science… Read more

Developing and Operationalizing H2O.ai Models with Azure

This post is authored by Daisy Deng, Software Engineer, and Abhinav Mithal, Senior Engineering Manager, at Microsoft. The focus on machine learning and artificial intelligence has soared over the past few years, even as fast, scalable and reliable ML and AI solutions are increasingly viewed as being vital to business success. H2O.ai has lately been… Read more

Saving Snow Leopards with Deep Learning and Computer Vision on Spark

This post is authored by Mark Hamilton, Software Engineer at Microsoft, Rhetick Sengupta, President of Snow Leopard Trust, and Principal Program Manager at Microsoft, and Roope Astala, Senior Program Manager at Microsoft. The Snow Leopard – A Highly Endangered Animal Snow leopards are highly endangered animals that inhabit high-altitude steppes and mountainous terrain in Asia… Read more

Running BigDL Apache Spark Deep Learning Library on Microsoft Data Science Virtual Machine

This post is co-authored by Gopi Kumar at Microsoft and Sergey Ermolin at Intel. Introduction BigDL is a distributed deep learning library for Apache Spark. It has both Python and Scala interfaces and takes advantage of Spark-enabled distributed compute infrastructure, allowing users to write Deep Learning applications in a familiar native Spark context format. The Microsoft… Read more

Announcing Microsoft Machine Learning Library for Apache Spark

This post is authored by Roope Astala, Senior Program Manager, and Sudarshan Raghunathan, Principal Software Engineering Manager, at Microsoft. We’re excited to announce the Microsoft Machine Learning library for Apache Spark – a library designed to make data scientists more productive on Spark, increase the rate of experimentation, and leverage cutting-edge machine learning techniques –… Read more

End-to-End Scenarios Enabled by the Data Science Virtual Machine: Webinar Video

This post is authored by Barnam Bora, Program Manager in the Algorithms & Data Science team at Microsoft. Microsoft’s Data Science Virtual Machine (DSVM) is a family of popular VM images in Windows Server & Linux flavors that are published on the Microsoft Azure Marketplace. They have a curated but broad set of pre-configured machine… Read more

Build & Deploy Machine Learning Apps on Big Data Platforms with Microsoft Linux Data Science Virtual Machine

This post is authored by Gopi Kumar, Principal Program Manager in the Data Group at Microsoft. This post covers our latest additions to the Microsoft Linux Data Science Virtual Machine (DSVM), a custom VM image on Azure, purpose-built for data science, deep learning and analytics. Offered in both Microsoft Windows and Linux editions, DSVM includes… Read more

Announcing Microsoft R on Apache Spark and R Client at the Hadoop Summit

This post was authored by Nagesh Pabbisetty, Partner Director of PM, Microsoft R. This week Microsoft will be joining thousands of people attending Hadoop Summit in San Jose to explore the technology and business of big data and data science. As part of our participation in the conference, I’m happy to announce today that Microsoft… Read more