AI & ML
MLOps: Deploy & Monitor ML Models
Take ML models from notebook to production
About This Workshop
Master ML lifecycle: experiment tracking, model versioning, containerization, CI/CD for ML, model serving, drift monitoring, and A/B testing. Tools: MLflow, Kubeflow, Docker, and SageMaker.
About Nikhil Agarwal
MLOps Lead at Swiggy. Built the ML platform powering Swiggy's recommendation and delivery optimization systems.
₹99
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