From MLOps Theory to Implementation

Launching your ML project begins far before model development. Tradeoffs, context, and team culture will determine your machine learning operations (MLOps) and path to success.

Learn how to go from MLOps theory to implementing a robust framework, including:

Developing an AI-first mindset
The end-to-end MLOps lifecycle
Calculating ROI of MLOps

Two-page healthcare AI checklist showing Part 1: Foundational Setup & Risk Assessment with steps for AI governance, principles, inventory, and risk tiers, and Part 2: Pre-Deployment Evaluation & Go-Live Checks with validation for predictive models; includes an astronaut illustration interacting with futuristic AI health data dashboards.

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