Deploying Deep Learning Models on Kubernetes with GPUs

This post is authored by Mathew Salvaris and Fidan Boylu Uz, Senior Data Scientists at Microsoft. One of the major challenges that data scientists often face is closing the gap between training a deep learning model and deploying it at production scale. Training of these models is a resource intensive task that requires a lot… Read more

Inventory Optimization Solution in the Azure AI Gallery

This post is co-authored by Dmitry Pechyoni, Senior Data Scientist, Hong Lu and Chenhui Hu, Data Scientists, Praneet Solanki, Software Engineer, and Ilan Reiter, Principal Data Scientist Manager at Microsoft. For retailers, inventory optimization is a critical task to facilitate production planning, cost reduction, and operation management. Tremendous business value can be derived by optimizing… Read more

Intelligent Edge: Building a Skin Cancer Prediction App with Azure Machine Learning, CoreML & Xamarin

This post is authored by Anusua Trivedi, Carlos Pessoa, Vivek Gupta & Wee Hyong Tok from the Cloud AI Platform team at Microsoft. Motivation AI has emerged as one of the most disruptive forces behind digital transformation and it is revolutionizing the way we live and work. AI-powered experiences are augmenting human capabilities and transforming… Read more

Training Many Anomaly Detection Models using Azure Batch AI

This post is authored by Said Bleik, Senior Data Scientist at Microsoft. In the IoT world, it’s not uncommon that you’d want to monitor thousands of devices across different sites to ensure normal behavior. Devices can be as small as microcontrollers or as big as aircraft engines and might have sensors attached to them to… Read more

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 PyImageSearch.com 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: 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

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