Every premium and members-only resource for $9.99/month, as a no-commitment subscription. See the plans

PalateKit

Sign in
Menu

Request a resource

Describe the resource you are missing in one sentence. We will email you when it is published.

0 / 280

A page, a video or an image online.

Unlock PalateKit

Unlock everything

Plan

Paying means accepting our terms of sale.

Secure payment by Stripe. Receipts and invoices sent by email.

Welcome back

Sign in to install, download or save this resource. A free account is enough for free resources.

ML experimentation, tracking and production readiness v1.0.0

Use this resource to set up ML experiment tracking and judge whether a model is ready for production

New

  • 525 downloads
  • 175 likes
  • 123 saves

Free

Install with the CLI

In a terminal, from the folder you want:

npx --yes palatekit@latest install ml-experiment-tracking-readiness

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 applies the experimentation conventions: environment, repository structure, experiment tracking, dataset and model abstractions, then a production-readiness review. You get a reproducible setup and a checklist to pass before deployment.

Mostly picked by

Updated November 2, 2026

Card for the “ML experimentation, tracking and production readiness” skill

Details

Works in
Install guides
Generates with
Your agent's model
Licence
CC-BY-4.0

Similar resources

View all

What you get

  • references/model-experimentation.md: model experimentation conventions
  • references/provenance.md: traceability and reproducibility
  • references/ml-checklists.md: ML checklists

Good fit for

  • You are setting up an experimentation environment for a data team
  • A trained model must be assessed before it goes to production

Not for

    Tags

    • machine learning
    • tracking
    • reproducibility
    • production
    • model

    About

    You say

    “Check whether our scoring model is production-ready against the ML checklist.”

    Card for the “ML experimentation, tracking and production readiness” skill

    Skill published by microsoft under the CC-BY-4.0 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 set up ML experiment tracking and judge whether a model is ready for production
    3. Review and adjust the result

    Content preview

    Files

    • LICENSE1.1 KB
    • NOTICE-PALATEKIT.md0.5 KB
    • references/ml-checklists.md6.3 KB
    • references/model-experimentation.md8.3 KB
    • references/provenance.md6.1 KB
    • SKILL.md6.8 KB

    Origin and licence

    Listed unmodified

    Author
    microsoft
    Source
    github.com/microsoft/hve-core/tree/854593cab3f35b3c57035c88794b705b4b64e6a0/.github/skills/data-science-engineering/ml-experimentation
    Licence
    CC-BY-4.0

    Notice

    « ml-experimentation » (microsoft, CC-BY-4.0) livré dans sa version d'origine : fiche en français et en anglais par PalateKit.

    User reviews

    –

    No ratings yet

    Loading reviews…

    Delete your review?

    Your rating and comment will be removed from the page.