Microsoft AI-Powered Assistant Copilot Will Be Accessible Through Windows Taskbar
On Tuesday, Microsoft announced that it is building an AI chat interface directly into the Windows operating system. Some of the features users can expect are music suggestions, document summarization, tech support, and answering questions similar to their search engine Bing. This is yet another major... Read more
ODSC & Microsoft March 2023 Recap – Blogs and Webinars
Over the past year, Microsoft has been releasing a lot of free content on ODSC channels, from webinars to blog posts. If you haven’t yet, now’s the time to check out what they’ve been up to. Webinars Responsible AI Mitigations and Tracker: New open-source tools for... Read more
Using Azure ML to Train a Serengeti Data Model for Animal Identification
Article on Azure ML by Bethany Jepchumba and Josh Ndemenge of Microsoft In this article, I will cover how you can train a model using Notebooks in Azure Machine Learning Studio. To get the data, you will need to follow the instructions in the article: Create... Read more
GitHub Codespaces and GitHub Copilot: 2 Stories, Thousands of Possibilities
The year 2022 marked a turning point for GitHub and all its users, with the announcement of the general availability of two revolutionary services for developers: GitHub Codespaces and GitHub Copilot. A Codespace is a development environment hosted in the cloud and accessible via a web... Read more
Distributed training with PyTorch and Azure ML
By Beatriz Stollnitz, Principal Cloud Advocate at Microsoft Suppose you have a very large PyTorch model, and you’ve already tried many common tricks to speed up training: you optimized your code, you moved training to the cloud and selected a fast GPU VM, you installed software packages that... Read more
Faster Training and Inference Using the Azure Container for PyTorch in Azure ML
By Beatriz Stollnitz, Principal Cloud Advocate at Microsoft If you’ve ever wished that you could speed up the training of a large PyTorch model, then this post is for you! The Azure ML team has recently released the public preview of a new curated environment that... Read more
Training Your PyTorch Model Using Components and Pipelines in Azure ML
By Beatriz Stollnitz, Principal Cloud Advocate at Microsoft In this post, we’ll explore how you can take your PyTorch model training to the next level, using Azure ML. In particular, we’ll see how you can split your training code into multiple steps that can be easily... Read more
Getting Started with ML.NET
Article by Jasmine Greenaway and Carlotta Castelluccio of Microsoft. Machine learning (ML) is everywhere. We use ML-empowered applications every day: when choosing the next TV series to watch based on Netflix recommendations for example, or when asking Alexa to play our favorite song. Soon every application... Read more
Training and Deploying Your PyTorch Model in the Cloud with Azure ML
By Beatriz Stollnitz, Principal Cloud Advocate at Microsoft You’ve been training your PyTorch models on your machine, and getting by just fine. Why would you want to train and deploy them in the cloud? Training in the cloud will allow you to handle larger ML models... Read more
Enabling Resilient Machine Learning Systems
Article by Francesca Lazzeri and Bea Stollnitz of Microsoft. Resilient machine learning systems are fast, accurate, and flexible. They assist you in your day-to-day tasks for maximum efficiency, they leverage the latest software and hardware for the fastest performance, and they guide you through complex tasks... Read more