Training State-of-the-Art Neural Networks in the Microsoft Azure Cloud

This is the third post in a three-part series by guest blogger, Adrian Rosebrock. Adrian writes at about computer vision and deep learning using Python. He recently finished authoring a new book on deep learning for computer vision and image recognition. Introduction In the final part in this series, I want to address a question I received from… Read more

Scaling Azure Container Service Clusters

This post is authored by Daniel Grecoe, Senior Software Engineer at Microsoft. Replica sets and pods and nodes…oh my! Microsoft has created very powerful and customizable tools for the professional data scientist with the Azure Machine Learning Workbench. The tool is used to create container images for Machine Learning or Artificial Intelligence models and exposing… Read more

Demystifying Docker for Data Scientists – A Docker Tutorial for Your Deep Learning Projects

This post is authored by Shaheen Gauher, Data Scientist at Microsoft. Data scientists who have been hearing a lot about Docker must be wondering whether it is, in fact, the best thing ever since sliced bread. If you too are wondering what the fuss is all about, or how to leverage Docker in your data… Read more

Comparing Deep Learning Frameworks: A Rosetta Stone Approach

This post is authored by Ilia Karmanov, Mathew Salvaris, Miguel Fierro, Danielle Dean, all Data Scientists at Microsoft. With this blog post, we are releasing a full version 1.0 of this repo, open-source on GitHub at: We believe deep-learning frameworks are like languages: Sure, many people speak English, but each language serves its own… Read more

How Three Lines of Code and Windows Machine Learning Empower .NET Developers to Run AI Locally on Windows 10 Devices

This post is authored by Rosane Maffei Vallim, Program Manager, and Wilson Lee, Senior Software Engineer at Microsoft. Artificial Intelligence (AI) with deep learning and machine learning algorithms are changing the way we solve variety of problems from manufacturing to biomedical industries. The applications that can benefit from the power of AI are endless. With… Read more

Pixel-Level Land Cover Classification Using the Geo AI Data Science Virtual Machine and Batch AI

This post was authored by Mary Wahl, Kolya Malkin, Siyu Yang, Patrick Flickinger, Wee Hyong Tok, Lucas Joppa, and Nebojsa Jojic, representing the Microsoft Research and AI for Earth teams. Last week Microsoft launched the Geo AI Data Science Virtual Machine (DSVM), an Azure VM type specially tailored to data scientists and analysts that manage… Read more

ONNX Models to be Runnable Natively on 100s of Millions of Windows Devices

This post was authored by Eric Boyd, CVP, AI Data & Infrastructure. Today Microsoft is announcing the next major update to Windows will include the ability to run Open Neural Network Exchange (ONNX) models natively with hardware acceleration. This brings 100s of millions of Windows devices, ranging from IoT edge devices to HoloLens to 2-in-1s… Read more

Using Microsoft AI to Build a Lung-Disease Prediction Model Using Chest X-Ray Images

This blog post is co-authored by Xiaoyong Zhu, George Iordanescu and Ilia Karmanov, Data Scientists at Microsoft, and Mazen Zawaideh, Radiologist Resident at the University of Washington Medical Center. Introduction Artificial Intelligence (AI) has emerged as one of the most disruptive forces behind digital transformation that is revolutionizing the way we live and work. This… Read more

Image Data Support in Apache Spark

This post is co-authored by the Microsoft Azure Machine Learning team, in collaboration with Databricks Machine Learning team. Introduction Apache Spark is being increasingly used for deep learning applications for image processing and computer vision at scale. Problems such as image classification or object detection are being solved using deep learning frameworks such as Cognitive… Read more

Now Available: Access to Source Code & Demos of AI-Infused Apps

This post is authored by Tara Shankar Jana, Senior Technical Product Marketing Manager at Microsoft. The success of enterprises in adopting AI to solve real-world problems hinges on bringing a comprehensive set of AI services, tools and infrastructure to every developer, so they can deliver AI-powered apps of the future that offer unique, differentiated and… Read more