Claude Code plugins
6 plugins from public Claude Code marketplaces. Each one bundles skills, slash commands, agents, hooks or MCP servers that install together.
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ML model training pipelines, hyperparameter tuning, model deployment automation, experiment tracking, and MLOps workflows
Twelve MLSys-specific skills for machine-learning-and-systems conference submission strategy, grounded in the official MLSys 2026 Call for Research Papers, Industrial Track CFP, Call for Artifact Evaluations, and dates/organization pages.
academic
SQL, analytics, datasets, models and machine-learning workflows.
ML pipeline design, experiment tracking, model evaluation, training debugging, and reproducibility.
developer tools
12 working methods for machine learning: cross-validation, drift-monitoring, experiment-tracking, feature-engineering, and more
Design and improve human annotation programs for machine-learning training, validation, and evaluation data, including task and label schemas, active acquisition, annotator guidance, calibration, disagreement, adjudication, provenance, and cost-quality stopping. Do not use for general statistical inference, data storage pipelines, model training, or annotation-interface implementation; route those concerns to data-scientist, data-engineering, ml-engineering, or product-design-and-ux.
