Machine learning operations (MLOps) is one of the fastest growing subfields of artificial intelligence. In this course, instructor Kumaran Ponnambalam shows you how to deploy and monitor ML models to create structured, improved outcomes in your everyday workflow.
Learn how to implement MLOps to:
- Create smooth upgrades of models in production on your next machine learning project.
- Ensure continuous delivery with deployment pipelines, rollout strategies, infrastructure, and best practices.
- Pattern, scale, build resilience, optimize, and utilize automation management tools for model serving.
- Use monitoring pipelines, observability, metrics, production data, alerts, and thresholds for continuous monitoring.
- Manage concept drift and feature drift, retraining models when necessary.
- Practice effective, fair, explainable, secure, and responsible artificial intelligence.