Learn Semantic Caching for AI Agents with DeepLearning.AI

We worked with our friends over at DeepLearning.AI to bring you "Semantic Caching for AI Agents," a 75-minute course lead by Tyler Hutcherson and Iliya Zhechev that teaches you how to build a semantic cache using Redis to make AI systems faster and more cost effective. Using seven different video lessons and four code examples, you’ll learn to: ➡️ Build your first semantic cache from scratch – Build a working cache to see how each component works, then implement it using Redis’ open source tools. ➡️ Measure cache effectiveness with key metrics – Track cache hit rate, precision, recall, and latency to understand your cache’s real impact. ➡️ Enhance cache accuracy with advanced techniques – Use threshold tuning, cross-encoders, LLM validation, and fuzzy matching to make your cache more effective. ➡️ Build a fast AI agent with semantic caching – Integrate semantic caching into an AI agent that reuses results, skips redundant work, and gets faster over time. Start building today: https://lnkd.in/gxGSKuwj