Welcome back to our real-time sentiment analysis series! In Part 1, we established the event-driven architecture foundation. Now, let’s dive deep into the AI processing
Category: AI
Azure OpenAI Service: Integration Patterns and Best Practices for Enterprise Applications
Learn proven integration patterns and best practices for implementing Azure OpenAI Service in enterprise applications. Covers security, performance optimization, cost management, and common pitfalls to avoid.
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
Expectation-Maximization (EM) Algorithm: Mastering Statistical Learning with Hidden Variables
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
Support Vector Machine (SVM): The Mathematical Powerhouse of Classification
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
