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

Machine Learning for Developers – How to Build Intelligent Apps & Services

This post is authored by Daniel Grecoe, Senior Software Engineer at Microsoft. There’s a lot of talk about machine learning these days and how it will transform applications and services. Most of it is right on target: ML is definitely changing the way certain computing tasks will be implemented in the future, why wouldn’t it?… 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

Loading a Trained Model Dynamically in an Azure ML Web Service

This post is authored by Ahmet Gyger, Program Manager at Microsoft. We are very excited to announce the availability of a new module named “Load Trained Model”. As its name indicates, this module allows you to load a trained model (also referred to as an iLearner file) in Azure ML into an experiment at runtime…. 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

Introducing the new Data Science Virtual Machine on Windows Server 2016

This post is authored by Udayan Kumar, Software Engineer at Microsoft. We are excited to offer a Windows Server 2016 version of our very popular Microsoft Azure Data Science Virtual Machine (DSVM). This new DSVM version is based on the latest Windows Server 2016 Data Center edition. We’ve added new tools and upgraded existing tools… Read more

GA of Cognitive Toolkit 2.0 – Microsoft’s Open Source, Enterprise-Ready, TensorFlow-Outperforming AI Toolkit

Re-posted from the Microsoft Next blog and the Cognitive Toolkit blog. We’re excited to announce the general availability of Cognitive Toolkit 2.0, Microsoft’s open source, enterprise-ready, production-grade AI offering. Cognitive Toolkit allows users to create, train, and evaluate their own neural networks that can then scale efficiently across multiple GPUs and machines on massive data… Read more

Deployment of Pre-Trained Models on Azure Container Services

This post is authored by Mathew Salvaris, Ilia Karmanov and Jaya Mathew. Data scientists and engineers routinely encounter issues when moving their final functional software and code from their development environment (laptop, desktop) to a test environment, or from a staging environment to production. These difficulties primarily stem from differences between the underlying software environments… Read more

“Serving AI with Data” – Recap of the Microsoft AI Immersion Workshop

Artificial Intelligence is enjoying its day in the sun. AI-related articles are now routinely featured as front page news and the technology is being used in an ever growing variety of applications, including in conversational bots, autonomous vehicles, connected machines, in medical diagnosis and much more. AI is therefore of growing interest to millions of… 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