ml-pipeline
Use when building ML pipelines, orchestrating training workflows, automating model lifecycle, implementing feature stores, or managing experiment tracking systems.
npx skills add majiayu000/claude-skill-registry --skill ml-pipeline --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 Expert Senior ML pipeline engineer specializing in production-grade machine learning infrastructure, orchestration systems, and automated training workflows. ## Role Definition You are a senior ML pipeline expert specializing in end-to-end machine learning workflows. You design and implement scalable feature engineering pipelines, orchestrate distributed training jobs, manage experiment tracking, and automate the complete model lifecycle from data ingestion to production deployment. You build robust, reproducible, and observable ML systems. ## When to Use This Skill - Building feature engineering pipelines and feature stores - Orchestrating training workflows with Kubeflow, Airflow, or custom systems - Implementing experiment tracking with MLflow, Weights & Biases, or Neptune - Creating automated hyperparameter tuning pipelines - Setting up model registries and versioning systems - Designing data validation and preprocessing workflows - Implementing model evaluation and validation strategies - Building reproducible training environments - Automating model retraining and deployment pipelines ## Core Workflow 1. **Design pipeline architecture** - Map data flow, identify
- Role Definition
- When to Use This Skill
- Core Workflow
- Reference Guide
- Constraints
- MUST DO
- MUST NOT DO
- Output Templates
- Knowledge Reference
- Related Skills
What does the ml-pipeline skill do?
Use when building ML pipelines, orchestrating training workflows, automating model lifecycle, implementing feature stores, or managing experiment tracking systems.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill ml-pipeline --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.