Explore comprehensive implementation of Variational Quantum Eigensolver (VQE) in Azure Quantum. Learn how to build production-ready quantum machine learning workflows with Python, Node.js, and C# code examples, optimization strategies, and enterprise integration patterns for solving complex problems in chemistry and materials science.
Category: Machine Learning
Azure AI Foundry Deep Dive Series Part 4: Custom Model Training and Fine-Tuning Workflows
Master custom model training in Azure AI Foundry. Learn when to fine-tune versus prompt engineering, how to prepare high-quality training data, and implement production-ready fine-tuning workflows with serverless and managed compute options.
Azure AI Foundry Deep Dive Series: Introduction to Microsoft’s Unified AI Platform
Discover Azure AI Foundry, Microsoft’s unified platform for building, deploying, and managing enterprise AI applications. This comprehensive introduction covers architecture, capabilities, and recent innovations that make it the go-to platform for production AI systems in 2025.
Advanced MediaPipe: Custom Models, Training, and Extending the Framework
Master advanced MediaPipe techniques including custom model training, enterprise deployment, and framework extension. Learn to build production-scale computer vision systems with monitoring, optimization, and scalability.
CART Algorithm: The Foundation of Interpretable Machine Learning and Decision Trees
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: The Surprisingly Effective Probabilistic Classifier Behind Spam Filters
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
k-Nearest Neighbors (kNN): The Intuitive Algorithm That Powers Recommendation Systems
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 Algorithm: The Revolutionary Ensemble Method That Changed Machine Learning
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 Algorithm: How Google Revolutionized Web Search and Network Analysis
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,
Apriori Algorithm: The Foundation of Association Rule Mining and Market Basket Analysis
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
