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Overview
Ready to learn how to deploy, operationalize, and monitor generative AI applications? This content will help you gain skills in the deployment of generative AI applications using tools like Model Serving. We’ll also cover how to operationalize generative AI applications following best practices and recommended architectures. Finally, we’ll discuss the idea of monitoring generative AI applications and their components using Lakehouse Monitoring.
N/A
Coming Soon...
Model Deployment Fundamentals Model Management Deployment Methods Batch Deployment Introduction to Batch Deployment Batch Inference Batch Inference Workflows using SLM Real-Time Deployment Introduction to Real-Time Deployment Databricks Model Serving Serving External Models with Model Serving Deploying an LLM Chain to Databricks Model Serving Custom Model Deployment and A/B Testing AI System Monitoring AI Application Monitoring Online Monitoring an LLM RAG Chain LLMOps Concepts MLOps Primer LLMOps vs MLOps
Model Deployment Fundamentals
Batch Deployment
Real-Time Deployment
AI System Monitoring
LLMOps Concepts
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