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Design leakage-safe ML data pipelines v1.0.0

Use this resource to design data and feature pipelines for machine learning

New

  • 359 downloads
  • 185 likes
  • 176 saves

Free

Install with the CLI

In a terminal, from the folder you want:

npx --yes palatekit@latest install ml-data-pipeline-design

With no option, the skill goes to ~/.agents/skills/; add --agent claude-code (or codex, cursor…) to target an agent.

First time: connect the CLI with

npx --yes palatekit@latest login

The agent sets pipeline invariants, picks the processing engine and configures features to avoid training-serving skew. You get a reproducible, controlled pipeline.

Mostly picked by

Updated November 2, 2026

Card for the “Design leakage-safe ML data pipelines” skill

Details

Works in
Install guides
Generates with
Your agent's model
Licence
MIT

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What you get

  • SKILL.md: pipeline invariants, ingestion and storage
  • SKILL.md: processing engines, Spark optimization and the Feast blueprint

Good fit for

  • You want to avoid training-serving skew
  • You are setting up a feature store with Feast

Not for

    Tags

    • pipeline
    • data
    • feature store
    • validation
    • ml

    About

    You say

    “Design the feature pipeline for my churn model, without time leakage.”

    Card for the “Design leakage-safe ML data pipelines” skill

    Skill published by josiahsiegel under the MIT license, delivered in its original version.

    Show more

    How to use it

    1. Install the skill in your agent's skills folder
    2. Ask your agent to design data and feature pipelines for machine learning
    3. Review and adjust the result

    Content preview

    Files

    • LICENSE1.1 KB
    • NOTICE-PALATEKIT.md0.5 KB
    • SKILL.md9.6 KB

    Origin and licence

    Listed unmodified

    Author
    josiahsiegel
    Source
    github.com/josiahsiegel/claude-plugin-marketplace/tree/5a1b1123b9e50aa9a66a61005ca6fe012cc7442d/plugins/ml-master/skills/ml-data-pipeline
    Licence
    MIT

    Notice

    « ml-data-pipeline » (josiahsiegel, MIT) livré dans sa version d'origine : fiche en français et en anglais par PalateKit.

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