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

How Stack Overflow Can Use Microsoft AI to Empower Every Developer

This post is authored by Anand Raman, Chief of Staff for the Cloud AI team at Microsoft. Artificial Intelligence has emerged as one of the most disruptive forces behind the digital transformation of business. Soon, most enterprises will depend on AI to enhance decision making, reinvent business models and ecosystems, and remake the customer experience…. Read more

Ignite 2017: Announcing Tools for AI-Driven Digital Transformation

Re-posted from the Microsoft Azure blog. Artificial Intelligence (AI) has emerged as one of the most disruptive forces behind the digital transformation of business. Earlier today, at Microsoft Ignite 2017, where we are in conversations about digital transformation with over 25,000 customers and partners, Joseph Sirosh, Corporate Vice President for Cloud Artificial Intelligence, shared the… Read more

Using the Team Data Science Process (TDSP) in Azure Machine Learning

This post is authored by Wei Guo, Data Scientist, Hai Ning, Principal PM Manager, Xibin Gao, Data Scientist, Brad Severtson, Senior Content Developer, and Debraj GuhaThakurta. Senior Data Scientist Lead, at Microsoft. In this post, we describe how the Team Data Science Process (TDSP) project structure and documentation templates can be instantiated and used in… Read more

Data Transformations “By Example” in the Azure Machine Learning Workbench

This post is authored by Ranvijay Kumar, Senior Program Manager at Microsoft. In this post, I talk about the Derive Column By Example transformation – an unexpected, powerful and super-efficient way to perform complex data transformations in the Azure Machine Learning Workbench. Imagine you’re head chef at a boutique restaurant where meals are prepared by… Read more

Deploying Machine Learning Models using Azure Machine Learning

This post is authored by Raymond Laghaeian, Principal Program Manager at Microsoft. Azure Machine Learning provides command line interfaces (CLIs) for deploying and managing machine learning models. CLIs provide an easy way to deploy trained ML models as web service APIs which you can use in web, mobile, and line-of-business applications. This includes running the… Read more