Build end-to-end MLOps pipelines from data preparation through model training, validation, and production deployment. Use when creating ML pipelines, implementing MLOps practices, or automating model training and deployment workflows.
6.9
Rating
0
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Machine Learning
Category
This skill provides a well-structured overview of MLOps pipeline orchestration with clear coverage of the full ML lifecycle. The description adequately conveys when to use the skill, and the document is logically organized with good separation of concerns (references to external files for detailed guides). However, the novelty score is moderate because much of this involves coordinating existing tools (Airflow, MLflow, etc.) that a CLI agent could invoke directly, and the skill provides more organizational guidance than complex automation. The task knowledge is solid with clear patterns and best practices, though actual implementation details are appropriately delegated to referenced files. Overall, this is a useful orchestration skill for complex ML workflows, but not highly novel in terms of unique capabilities.
wshobson
Skill Author
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