{"enrichment":{"faq":[{"a":"ML Engineering teaches you to build and operate production machine learning systems with guidance on model deployment, infrastructure setup, and monitoring. The skill covers MLOps workflows, LLM integration patterns, and best practices for scaling models in real-world environments.","q":"What does ML Engineering cover?"},{"a":"ML Engineering best practices include designing robust ML workflows and pipelines, implementing proper infrastructure for model deployment, establishing monitoring and maintenance protocols, and following MLOps principles. The skill emphasizes production-ready system design over experimental notebooks.","q":"What are ML engineering best practices?"},{"a":"ML Engineering guides you through machine learning pipeline setup by covering workflow design, data processing stages, model training orchestration, and deployment automation. 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