Browse Machine Learning Community (22)

Yongguang Zhang presents an in-depth view of Microsoft’s AI-powered RAN and intelligent edge strategy, showing how AI, Azure, and advanced platforms are set to revolutionize the future of telecom networks through automation, edge intelligence, and innovative new services.

Sally Dabbah explains how to orchestrate Azure Synapse Analytics pipelines for predictable execution on shared Spark pools. Key techniques include workload prioritization and adaptive orchestration strategies.

AnaviNahar introduces the general availability of Serverless Workspaces in Azure Databricks, detailing their architecture and guidance for when to choose Serverless or Classic models.

NaufalPrawironegoro shares engineering insights on building robust real-time data pipelines with Microsoft Fabric. Learn best practices for data quality, lag management, and operational foundations based on enterprise experiences.

kinfey presents a comprehensive exploration of building an agentic podcast studio using the Microsoft Agent Framework, local SLMs, and VibeVoice. This guide reveals how edge-first AI orchestration empowers privacy, speed, and scalable creative automation.

NaufalPrawironegoro demonstrates an advanced architecture for multi-store retail data ingestion using Microsoft Fabric, Delta Lake, and Azure Event Hubs. The guide explains operational workflows, automation patterns, and best practices for seamless store onboarding.

GeertVanTeylingen presents a comprehensive exploration of the Azure NetApp Files object REST API, demonstrating how it empowers direct analytics and AI access to enterprise file data via S3-compatible object interfaces.

Hannah Abbott details a demo application for healthcare organizations demonstrating how Azure AI powers real-time, secure transcription and clinical text analytics. Developed alongside Samuel Tauil, this solution helps teams streamline data workflows and analytics using Microsoft cloud technology.

Pamela Fox invites you to a free, six-part livestream series on building advanced AI agents in Python using the Microsoft Agent Framework. The series covers agent fundamentals, memory, RAG, workflow orchestration, monitoring, and HITL workflows with live demos and practical examples.

JohnGruszczyk discusses how Insilico Medicine’s Nach01 model integrates with Microsoft Discovery on Azure, enabling AI-driven, reproducible, and scalable drug discovery workflows for researchers.

lmiroslaw showcases how Neural Concept utilized Azure HPC and AI infrastructure to achieve record-setting accuracy and efficiency for industrial aerodynamic workflows, leveraging massive datasets and advanced machine learning techniques for real-world automotive impact.

Rafia Aqil and co-authors present a comprehensive technical guide to disaster recovery for Azure Databricks and Microsoft Fabric, focusing on automation, cloud resiliency, and best practices for DR in analytics platforms.

ravimodi demonstrates how teams can automate Azure Cosmos DB backups and enable instant data restoration before deployments using Azure Databricks, significantly improving agility and reducing downtime.

Rafia Aqil and colleagues deliver an in-depth migration playbook for cloud architects and BI developers, detailing how to approach Tableau to Power BI migration using a semantic layer-first methodology on Microsoft Fabric.

bhramesh demonstrates how to use Azure Key Vault to securely retrieve database connection strings in Databricks notebooks, focusing on reducing vulnerabilities and improving workflow security.

anishganguli shares a comprehensive technical guide to evaluating document processing pipelines using Microsoft AI services, covering everything from ground truth setup and OCR validation to precision-driven continuous improvement.

Chameseddine discusses hands-on solutions for managing state and avoiding race conditions in Azure serverless data pipelines, sharing lessons learned and design patterns from a real-world ETL challenge.

Sally Dabbah provides a technical walkthrough on implementing enterprise-grade data quality checks in Microsoft Fabric ETL pipelines, showcasing Great Expectations integration at every architecture layer.

anishganguli presents a detailed blueprint for extracting actionable, trusted data from large semi-structured documents using Azure AI technologies, focusing on scalable, context-aware pipelines and real-world evaluation.

Rafia Aqil, along with co-authors Amudha Palani and Peter Lo, provides a deep dive into end-to-end observability practices for Azure Databricks. This guide covers best practices for infrastructure and application logging across cloud-scale analytics workloads.