Tag: Data Science

How to Do Distributed Deep Learning for Object Detection Using Horovod on Azure

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This post is co-authored by Mary Wahl, Data Scientist, Xiaoyong Zhu, Program Manager, Siyu Yang, Software Development Engineer, and Wee Hyong Tok, Principal Data Scientist Manager, at Microsoft. Object detection powers some of the most widely adopted computer vision applications, from people counting in crowd control to pedestrian detection used by self-driving cars. Training an… Read more

AI Lab: Learn to Code with the Cutting-Edge Microsoft AI Platform

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This post is authored by Tara Shankar Jana, Senior Technical Product Marketing Manager at Microsoft. Among our exciting announcements at //Build, one of the things I was thrilled to launch is the AI Lab – a collection of AI projects designed to help developers explore, experience, learn about and code with the latest Microsoft AI… Read more

Deep Learning for Emojis with VS Code Tools for AI – Part 2

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This post is authored by Erika Menezes, Software Engineer at Microsoft. In Part 1 of this blog series, we created a recipe prediction model to predict recipes from a text input that may contain an arbitrary number of emojis. In this post we will go over how to operationalize this model as a web service… Read more

Free E-Book: A Developer’s Guide to Building AI Applications

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O’Reilly and Microsoft are excited bring you a new e-book on AI, titled A Developer’s Guide to Building AI Applications. This book, which is clearly developer-focused, walks you through the process of building intelligent cloud-based bots, and makes relevant code samples available from GitHub. As you know, AI is accelerating the digital transformation of every… Read more

How to Use FPGAs for Deep Learning Inference to Perform Land Cover Mapping on Terabytes of Aerial Images

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This post is authored by Mary Wahl, Data Scientist; Daniel Hartl and Wilson Lee, Senior Software Engineers; Xiaoyong Zhu, Program Manager; Erika Menezes, Software Engineer; and Wee Hyong Tok, Principal Data Scientist Manager, at Microsoft. AI for Earth puts Microsoft’s cloud and AI tools in the hands of those working to solve global environmental challenges…. Read more

Enterprise Deployment Tips for Azure Data Science Virtual Machine (DSVM)

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This post is authored by Gopi Kumar, Principal Program Manager at Microsoft. The Data Science Virtual Machine (DSVM), a popular VM image on the Azure marketplace, is a purpose-built cloud-based environment with a host of preconfigured data and AI tools. It enables data scientists and AI developers to iterate on developing high quality predictive models… Read more

Improving Medical Imaging Diagnostics Using Azure Machine Learning Package for Computer Vision

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This post is by Ye Xing, Senior Data Scientist, Tao Wu, Principle Data Scientist Manager, and Patrick Buehler, Senior Data Scientist, at Microsoft. The advancement of medical imaging, as in many other scientific disciplines, relies heavily on the latest advances in tools and methodologies that make rapid iterations possible. We recently witnessed this first-hand when… Read more

A Scalable End-to-End Anomaly Detection System using Azure Batch AI

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This post is authored by Said Bleik, Senior Data Scientist at Microsoft. In a previous post I showed how Batch AI can be used to train many anomaly detection models in parallel for IoT scenarios. Although model training tasks are usually the most demanding ones in AI applications, making predictions at scale on a continuous… Read more

Azure Machine Learning Packages for Vision, Text and Forecasting in Public Preview

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This post is authored by Matt Conners, Principal Program Manager, and Neta Haiby, Principal Program Manager at Microsoft. Earlier today, at Build 2018, we made a set of Azure AI Platform announcements, including the public preview release of Azure Machine Learning Packages for Computer Vision, Text Analytics, and Forecasting. The Azure Machine Learning Packages are… Read more

Kubernetes Load Testing

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This post is authored by Daniel Grecoe, Senior Software Engineer at Microsoft. Today many platforms are moving towards hosting artificial intelligence models in self-managed container services such as Kubernetes. At Microsoft this is a substantial change from Azure Machine Learning Studio which provided all the model management and operationalization services for the user automatically. To… Read more