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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
Evaluate ML Models with Azure Machine Learning’s Responsible AI Insights
In December 2021, we introduced the Responsible AI dashboard, a comprehensive experience bringing together several mature Responsible AI tools in the areas of data explorer (to proactively identify whether there is sufficient data representation for the variety of data subgroups), fairness assessment (to assess and identify... Read more
How to Connect Azure Synapse Analytics to Power BI 
The first question on your mind, well that is if you are unfamiliar with Azure Synapse Analytics is probably, what is Azure Synapse? Azure Synapse Analytics is an analytics service that enables you to bring together data integration, warehousing and big data analytics. Using Azure Synapse... Read more
MLOps V2 Solution Accelerator – Unifying MLOps at Microsoft
Article by Scott Donohoo and Setu Chokshi of Microsoft. MLOps means different things to different people, however, the fundamental essence of MLOps is to deliver models into productions faster with a consistent, repeatable, and reliable approach. Machine Learning Operations (MLOps) is key to accelerating how data... Read more
Many Models Training with Hyperparameter Optimization
This article presents an approach for you to train multiple machine learning models, optimizing the hyperparameters of each model in an automated way with Azure Machine Learning. Before getting into the part where I explain how to do this, let’s first get a better understanding of... Read more
How to Choose the Best GPU Optimized VM Sizes for Your Project on Azure
A common problem that data scientists face when training and deploying their machine learning models is the choice of the right type and size of hardware. Migrating machine learning tasks on the Cloud significantly simplified the data scientist’s job, who now just needs to login into... Read more
Azure Machine Learning CLI v2 and Python SDK v2
Azure Machine Learning is committed to simplifying the adoption of its platform for training and production cycles. Over the last several months, we have worked on adding support for workflows using command lines and support for scripts in multiple languages. We have also worked on bringing... Read more
AI Gets Bigger and Better: Microsoft’s AI-at-Scale Predictions
Two years ago, when Luis Vargas, Ph.D. of Microsoft AI addressed ODSC, he told the story of his daughter learning multiple languages as a small child and how this hidden complexity transferred to teaching machines to learn. The development of AI follows a similar path as... Read more
AIOps with Azure Metrics Advisor
Article by Tony Xing and Qiyang Li of Microsoft. AIOps is a term introduced by Gartner in 2016, referring to AI for IT Operations. It combines big data and machine learning to automate IT operations processes, including event correlation, anomaly detection, and causality determination. As more... Read more
Extracting Information From Unstructured Documents with Azure Form Recognizer
Extracting information from unstructured documents such as contracts is usually manual and involves tediously reading and understanding substantial amounts of documents to find specific information and manually extracting the information to digitize it. The process consumes a significant amount of a lawyer’s billable hours and is... Read more