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

Democratizing AI Through Microsoft Certifications in Data Science & Machine Learning

Posted by Marla Michel, Senior Program Manager for Ecosystem Development & Training at Microsoft. This blog is the first in a series where we will discuss several new certification exams for data professionals and the resources to prepare for them. When individuals decide which certification to take, their decision is typically based on their role… Read more

Now Serving: More AI with Your Big Data

Re-posted from the Microsoft SQL Server blog. Earlier today, at Build 2017, we made a string of announcements to further help developers and customers around the planet create breakthrough experiences through the power of artificial intelligence and big data. There were 3 major themes to these announcements: 1. AI at the Heart of the Microsoft… Read more

Monitoring Petabyte-Scale AI Data Lakes in Azure

This post by Reed Umbrasas, Software Engineer at Microsoft. Azure Data Lake Analytics lets customers run massively parallel jobs over petabytes of raw data stored in Azure Data Lake Store. During the recent Microsoft Data Amp event, we demonstrated how this massive processing power can be used to build a petabyte scale AI data lake… Read more

Text Mining to Improve the Health of Millions of Citizens

By Kenji Takeda, Director of Azure for Research at Microsoft. Doctors face daily decisions about the best care for their patients, and their own clinical experience can be enhanced using evidence-based medicine, such as through clinical trial data. As David Tovey, Editor-in-Chief, Cochrane, explained, “Before evidence-based medicine came along, people were reliant on the expertise… Read more

Empowering Every Organization on the Planet with Artificial Intelligence

Re-posted from the Microsoft SQL Server blog. Extracting intelligence from ever-expanding amounts of data is now the difference between being the next market disruptor versus being relegated to the history books. Microsoft’s comprehensive data platform and tools let developers and businesses create the next generation of intelligent applications, drive new efficiencies, create better products and… Read more

Accelerating Business Transformation with Cortana Intelligence Solution Templates

Earlier today, Joseph Sirosh, Corporate Vice President, Microsoft Data Group, announced a set of new Cortana Intelligence solution templates as part of his keynote address at the Microsoft Data Amp event. Cortana Intelligence solution templates give customers the means to rapidly conceive and implement their big data, machine learning and analytics projects. Technical implementers can… Read more

Deep Learning with Caffe2 on the Azure Data Science Virtual Machine

This post is authored by Gopi Kumar, Principal Program Manager, and Paul Shealy, Senior Software Engineer, at Microsoft. With the availability of ultra-fast GPUs (Graphics Processing Units), compute-intensive deep learning algorithms are becoming increasingly popular. Deep learning algorithms are particularly versatile at deriving insights from large amounts of information across rich formats such as text,… 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