Eliot Amal J shares his MLOps journey and insights.
Started with creativity and a hackathon, Eliot transitioned from full-stack development to MLOps.
Scaled MLOps practice by addressing gaps in documentation, architecture artifacts, MLOps operating model, impactful demos, and building bridges with ML platform providers and thought leaders.
MLOps is considered as the future of AI, bridging the gap between innovation and implementation.