GokuMohandas/mlops-course
Learn how to design, develop, deploy and iterate on production-grade ML applications.
Covers core ML workloads (data processing, model training, tuning, evaluation) through first-principles lessons that transition from interactive notebooks to production-ready Python scripts with testing and logging. Built on Ray for distributed computing across local laptops, Kubernetes, and cloud platforms (AWS/GCP), enabling seamless scaling without language switching. Integrates MLOps components including experiment tracking, CI/CD pipelines, and model serving while maintaining code parity between development and production environments.
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Aug 16, 2024
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