ml-pipeline-workflow
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 mod...
npx skills add majiayu000/claude-skill-registry --skill ml-pipeline-workflow-bcastelino-agent-skills-kit --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# ML Pipeline Workflow Complete end-to-end MLOps pipeline orchestration from data preparation through model deployment. ## Do not use this skill when - The task is unrelated to ml pipeline workflow - You need a different domain or tool outside this scope ## Instructions - Clarify goals, constraints, and required inputs. - Apply relevant best practices and validate outcomes. - Provide actionable steps and verification. - If detailed examples are required, open `resources/implementation-playbook.md`. ## Overview This skill provides comprehensive guidance for building production ML pipelines that handle the full lifecycle: data ingestion → preparation → training → validation → deployment → monitoring. ## Use this skill when - Building new ML pipelines from scratch - Designing workflow orchestration for ML systems - Implementing data → model → deployment automation - Setting up reproducible training workflows - Creating DAG-based ML orchestration - Integrating ML components into production systems ## What This Skill Provides ### Core Capabilities 1. **Pipeline Architecture** - End-to-end workflow design - DAG orchestration patterns (Airflow, Dagster, Kubeflow) - Component dependencies
- Do not use this skill when
- Instructions
- Overview
- Use this skill when
- What This Skill Provides
- Core Capabilities
- Reference Documentation
- Assets and Templates
- Usage Patterns
- Basic Pipeline Setup
- Production Workflow
- Best Practices
- Pipeline Design
- Data Management
What does the ml-pipeline-workflow skill do?
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 mod...
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill ml-pipeline-workflow-bcastelino-agent-skills-kit --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.