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Orchestrating an MLOps pipeline from data to deployment v1.0.0

Use this resource to orchestrate an end-to-end MLOps pipeline

New

  • 388 downloads
  • 204 likes
  • 177 saves

Free

Install with the CLI

In a terminal, from the folder you want:

npx --yes palatekit@latest install ml-pipeline-orchestration

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 designs the data preparation, training and model deployment pipeline and its orchestration. Some configuration templates and references are not included in this copy and must come from an existing installation before use. You get a pipeline architecture and its base configuration.

Mostly picked by

Updated November 2, 2026

Card for the “Orchestrating an MLOps pipeline from data to deployment” skill

Details

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

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What you get

  • SKILL.md: pipeline capabilities, usage patterns and base configuration
  • SKILL.md: external references to obtain (data preparation, training, execution graph)

Good fit for

  • Your models are trained by hand and hard to reproduce
  • You want a pipeline that runs from data to deployment

Not for

    Tags

    • mlops
    • pipeline
    • training
    • deployment

    About

    You say

    “Design an MLOps pipeline that retrains our recommendation model weekly and deploys it.”

    Card for the “Orchestrating an MLOps pipeline from data to deployment” skill

    Skill published by sickn33 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 orchestrate an end-to-end MLOps pipeline
    3. Review and adjust the result

    Content preview

    Files

    • LICENSE1.1 KB
    • NOTICE-PALATEKIT.md0.5 KB
    • SKILL.md9.2 KB

    Origin and licence

    Listed unmodified

    Author
    sickn33
    Source
    github.com/sickn33/agentic-awesome-skills/tree/e9809578fd426a284af017c5db99f8eb6628e6ca/skills/ml-pipeline-workflow
    Licence
    MIT

    Notice

    « ml-pipeline-workflow » (sickn33, MIT) livré dans sa version d'origine : fiche en français et en anglais par PalateKit.

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