Learn how to navigate technical debt in AI projects, balance rapid adoption with long-term sustainability, and implement best practices for successful AI initiatives.
Explore concepts of AI-driven query processing, key algorithms that enhance search performance, and best practices for optimizing AI-powered retrieval systems.
Explore key strategies for effective data management in AI projects, including real-time access, federated queries, and data literacy for developers and engineers.
Learn about context-specific real-time Generative AI (GenAI) with Retrieval Augmentation Generation (RAG) using Kafka and Flink to prevent hallucinations.
Develop a custom Sketch-to-Image API for converting hand-drawn/digital sketches into photorealistic images using stable diffusion models powered by ControlNet.
Experts at Black Hat 2024 reveal how developers and security pros can collaborate better: from shifting left to embracing AI and prioritizing user experience.
The Confusion Matrix and the ROC Curve evaluate model performance in machine learning and data science. Compare and learn when to use each in model evaluation.
Follow the steps outlined in this multi-part series to start with Semantic Kernel and integrate intelligent, context-aware functionalities into your projects.
Before our AI meal planner is complete, one crucial step remains: a taste test. This is where a robust evaluation framework becomes your most valuable tool.