Community
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Weekly Microsoft Learning Rooms Community Roundup (8/7)
JulieSirrine shares a curated summary of activities from Microsoft Learning Rooms, spotlighting hands-on community events and technical discussions covering Azure, AI, Fabric, Power BI, cloud security, and coding topics for Microsoft professionals.
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Semantic Clinic: A Math-First, Model-Agnostic Map for Diagnosing AI Failures
wfgy_engine presents the Semantic Clinic, an MIT-licensed, math-first guide for diagnosing and repairing AI system failures, with reproducible methods and model-agnostic applicability.
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Deploying Azure Foundry AI Agents via API for Web Integration
Luisio93’s community post explores practical steps to deploy Azure Foundry AI Agents and connect them to a Laravel front end, highlighting requirements for API integration and sharing deployment insights.
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From Space to Subsurface: Predicting Gold Zones with Azure AI and Machine Learning
MeysamRouhnavaz presents a hands-on case study using Azure AI and Machine Learning to predict gold-rich zones from satellite data, demonstrating the full data science workflow from preprocessing to production in mineral exploration.
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Challenges with Application Insights Diagnostic Settings and Stream Analytics File Updates
GarseBo describes challenges with Azure Application Insights diagnostic settings writing logs to a single file per hour, causing Stream Analytics to process incomplete data. The post focuses on possible workarounds and improvements.
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How to Quickly Catch and Clean Bad Data for AI Agents with VS Code Data Wrangler
AngelosPetropoulos offers practical advice on catching and fixing bad data before it disrupts your AI agent, highlighting the use of VS Code Data Wrangler for rapid, code-free dataset inspection and cleaning.
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GSPO vs. GRPO: Sequence-Level Reinforcement Learning for LLM Fine-Tuning
MarketingNetMind compares GSPO and GRPO, two reinforcement learning approaches for LLM fine-tuning, examining their variance, scalability, and real-world results in Mixture-of-Experts models.
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FinOps hubs 12: Non-Breaking Schema Versioning and FOCUS 1.2 Alignment
Michael Flanakin shares a deep dive into FinOps hubs 12, highlighting new approaches to schema versioning and alignment with FOCUS 1.2 for seamless Azure cost management and reporting.
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How Microsoft Azure and Qumulo Enable Cloud-Native File Systems for Enterprise Data Management
dukicn examines how Azure and Qumulo deliver cloud-native enterprise file storage. The article covers architectural options, migration tools, scalability, security features, and integration for AI and HPC workloads.
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Structuring a GNN-Based Next Activity Prediction for Business Process Mining
Street_Car_1297 seeks community input on designing a GNN solution for next activity prediction in business process mining, sharing project structure, dataset specifics, and open modeling questions.
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AI Data Governance Made Easy: How Microsoft Purview Tackles GenAI Risks and Builds Trust
Authored by vicperdana, this article explores how Microsoft Purview streamlines AI data governance and compliance, mitigating GenAI risks for enterprises.
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Navigation Property Best Practices in C#
In this community post, drld21 seeks input on best practices for navigation properties in C#. The article invites a discussion on the effective use of navigation properties in .NET applications, with a focus on real-world examples.
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Learning Real-World Complexity as a Jr. .NET Backend Developer
Author Adjer_Nimossia recounts the sobering realization that comes with tackling complex backend endpoints in .NET. They seek advice from the community on navigating the leap from basic CRUD to more advanced architectural challenges.
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Converting Page or Append Blobs to Block Blobs with Azure Data Factory
In this article, SaikumarMandepudi explains how to use Azure Data Factory to convert page or append blobs into block blobs, enabling access tier changes and storage cost optimization.
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Boosting Performance with the Materialized View Pattern in Azure
Authored by JohnNaguib, this article delves into the Materialized View pattern and its application in Microsoft Azure for optimizing data system performance.
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Confidence Score Decline in Document Intelligence Custom Extraction Models with New Layouts
aristotelisc describes an experiment using Azure Document Intelligence to train custom extraction models, highlighting how introducing new document layouts led to persistent confidence score drops. The author seeks community insights on this behavior.
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Workaround for Azure ARM 800 Resource Limit When Deploying Data Factory
jessred99 raises a challenge in deploying Azure Data Factory via Azure DevOps CI/CD pipelines, encountering the ARM 800 resource limit.