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Advanced Prompt Engineering Patterns for Claude in Azure AI Foundry
Model Context Protocol Part 4: Enterprise Integration Patterns – Security, Scaling, and Production Deployment
Model Context Protocol Part 3: Building MCP Servers in Node.js and C# – Cross-Platform Implementation Guide
Model Context Protocol Part 2: Building Your First MCP Server with Python and FastMCP
Model Context Protocol Part 1: Understanding the New Standard for AI-Data Integration
Vector Databases Part 8: Lessons Learned and Reality Check
How to Setup Docker: Complete Installation Guide for Linux, Windows, and macOS
Vector Databases Part 7: Production Deployment Patterns and Operations
Vector Databases Part 6: GraphRAG Architecture and Knowledge Graphs
Vector Databases Part 5: Advanced Optimization and Reranking Strategies 
Deciding between Azure Functions and Traditional APIs? This comprehensive guide compares costs, performance, and use cases with practical code examples to help you choose the right serverless strategy for your applications.
In 2025, Azure Cognitive Services has evolved into an even more powerful suite of AI capabilities that enables developers to build intelligent applications with minimal
As we navigate through 2025, Azure development with C# has reached new heights of sophistication. The ecosystem has evolved dramatically, offering developers unprecedented capabilities for
CART (Classification and Regression Trees) stands as one of the most interpretable and versatile algorithms in machine learning. Developed by Leo Breiman and colleagues in
Naïve Bayes stands as one of the most elegant and surprisingly effective algorithms in machine learning, despite its “naïve” assumption of feature independence. This probabilistic
The k-Nearest Neighbors (kNN) algorithm stands as one of the most intuitive and fundamentally simple algorithms in machine learning, yet it remains remarkably effective across
AdaBoost (Adaptive Boosting) revolutionized machine learning by proving that combining many weak learners could create a remarkably strong classifier. Developed by Yoav Freund and Robert
PageRank revolutionized the internet and became the foundation of Google’s search empire. This elegant algorithm, developed by Larry Page and Sergey Brin at Stanford University,
The Apriori algorithm revolutionized market basket analysis and association rule mining when it was introduced in 1994. This groundbreaking algorithm helps discover relationships between different
CART (Classification and Regression Trees) stands as one of the most interpretable and versatile algorithms in machine learning. Developed by Leo Breiman and colleagues in
