Anaconda and Microsoft Partner to Offer Python and R for Powerful Machine Learning

This post was authored by Nagesh Pabbisetty, Partner Director of Program Management, Microsoft Machine Learning Services. Recently, at Strata Data Conference in New York City, Microsoft and Anaconda announced an exciting partnership to make Anaconda Python distribution into SQL Server, Machine Learning Server, Azure Machine Learning, and Visual Studio to deliver real-time insights. In addition,… Read more

AI for Education: Individualized Code Feedback for Thousands of Students

This post is authored by Matthew Calder, Senior Business Strategy Manager, and Ke Wang, Research Intern at Microsoft. There are more than 9,000 students enrolled in the Microsoft Introduction to C# course on edX.org. Although course staff can’t offer the type of guidance available in an on-campus classroom setting, students can receive personalized help, thanks… Read more

Free Webinars on Cognitive Toolkit with Batch AI, DSVM & Document Collection Analysis

Join us at a set of three exciting webinars starting on Tuesday next week where we’ll show you how to train distributed convolution neural networks using Microsoft Cognitive Toolkit (aka CNTK) and Batch AI, how to do AI development using the latest version of the Data Science Virtual Machine (DSVM), and how to use Document… Read more

Announcing the Data Science Virtual Machine in Batch AI Service

This post is authored by Paul Shealy, Senior Software Engineer at Microsoft. We are pleased to announce the integration of the Microsoft Data Science Virtual Machine (DSVM) with the Batch AI service in Azure. DSVM is a family of popular VM images published on Azure with a broad choice of machine learning, AI and data… Read more

The Microsoft Team Data Science Process (TDSP) – Recent Updates

This post is authored by Xibin Gao, Data Scientist, Wei Guo, Data Scientist, Brad Severtson, Senior Content Developer, and Debraj GuhaThakurta, Senior Data Scientist Lead, at Microsoft What is TDSP Improving the efficiency of developing and deploying data science solutions requires an efficient process to complement the data platforms and data science tools that you… Read more