MLOps, LLMOps & Model Hub: Managing AI Models in Production

Training a model is half the work. Getting it into production and keeping it reliable is where the real operational complexity lives. Terms covered: - MLOps: deployment, versioning, monitoring and retraining. What DevOps did for software engineering, MLOps does for machine learning. - LLMOps: the same principles extended to language models, adding prompt versioning, token cost control, hallucination monitoring and context window limits - Model Hub: a central repository where models are published, discovered, versioned and deployed from one place Without a model hub, models scatter across teams and machines with no visibility into what is running where, or which version is live. — AI Fundamentals Glossary | H2O.ai University Full playlist: https://www.youtube.com/playlist?list=PLAWKlIKS-66E Free courses and certifications: https://h2o.ai/university #MLOps #LLMOps #AIinProduction #AIGlossary #H2Oai