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: https://github.com/ilkarman/DeepLearningFrameworks. We believe deep-learning frameworks are like languages: Sure, many people speak English, but each language serves its own… 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

ICYMI: Recent Microsoft AI Platform Updates, Including in ONNX, Deep Learning, Video Indexer & More

Four recent Microsoft posts about AI developments, just in case you missed it. 1. Getting Started with Microsoft AI – MSDN Article This MSDN article, co-authored by Joseph Sirosh and Wee Hyong Tok, provides a nice summary of all the capabilities offered by the Microsoft AI platform and how you can get started today. From… 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

Introducing Microsoft Machine Learning Server 9.2 Release

This post is authored by Nagesh Pabbisetty, Partner Director of Program Management at Microsoft. Earlier this year, Microsoft CEO Satya Nadella shared his vision for Microsoft and AI, pointing to Microsoft’s beginnings as a tools company, and our current focus on democratizing AI by putting tools “in the hands of every developer, every organization, every… Read more

How to Train & Serve Deep Learning Models at Scale, Using Cognitive Toolkit with Kubernetes on Azure

This post is authored by Wee Hyong Tok, Principal Data Science Manager at Microsoft. Deep Learning has fueled the emergence of many practical applications and experiences. It has played a central role in making many recent breakthroughs possible, ranging from speech recognition that’s reached human parity in word recognition during conversations, to neural networks that… 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

Deep Learning on the New Ubuntu-Based Data Science Virtual Machine for Linux

Authored by Paul Shealy, Senior Software Engineer, and Gopi Kumar, Principal Program Manager, at Microsoft. Deep learning has received significant attention recently for its ability to create machine learning models with very high accuracy. It’s especially popular in image and speech recognition tasks, where the availability of massive datasets with rich information make it feasible… Read more

Embarrassingly Parallel Image Classification, Using Cognitive Toolkit and TensorFlow on Azure HDInsight Spark

This post is by Mary Wahl, Data Scientist, T.J. Hazen, Principal Data Scientist Manager, Miruna Oprescu, Software Engineer, and Sudarshan Raghunathan, Principal Software Engineering Manager, at Microsoft. Summary Deep neural networks (DNNs) are extraordinarily versatile and increasingly popular machine learning models that require significantly more time and computational resources for execution than traditional approaches. By… Read more