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Hyperparameter tuning for ML models v1.0.0

Use this resource to search for the hyperparameters that maximize a model's performance

New

  • 309 downloads
  • 142 likes
  • 114 saves

Free

Install with the CLI

In a terminal, from the folder you want:

npx --yes palatekit@latest install hyperparameter-search-tuning

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 analyzes the model and target metric, picks a search strategy (grid, random or Bayesian) and explores the parameter space. You get a retained configuration, a search-space template and a visualization template.

Mostly picked by

Updated November 2, 2026

Card for the “Hyperparameter tuning for ML models” skill

Details

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

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What you get

  • SKILL.md: method, when-to-use guidance and examples (random forest, Bayesian optimization)
  • assets/: hyperparameter-space template in JSON and HTML visualization template

Good fit for

  • You want to tune a random forest without trying values by hand
  • You compare grid, random and Bayesian search on the same budget

Not for

    Tags

    • hyperparameters
    • machine learning
    • optimization
    • bayesian search

    About

    You say

    “Tune my random forest with Bayesian optimization to maximize accuracy.”

    Card for the “Hyperparameter tuning for ML models” skill

    Skill published by Jeremy Longshore <jeremy@intentsolutions.io> 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 search for the hyperparameters that maximize a model's performance
    3. Review and adjust the result

    Content preview

    Files

    • assets/hyperparameter_space_template.json2.8 KB
    • assets/README.md0.3 KB
    • assets/visualization_template.html2.7 KB
    • LICENSE1.1 KB
    • NOTICE-PALATEKIT.md0.5 KB
    • references/README.md0.1 KB
    • scripts/README.md0.8 KB
    • SKILL.md4.7 KB

    Origin and licence

    Listed unmodified

    Author
    Jeremy Longshore <jeremy@intentsolutions.io>
    Source
    github.com/jeremylongshore/tons-of-skills-marketplace/tree/ab85a061f7bcc039dac13ee193de7a4cd4388571/skills/.curated/tuning-hyperparameters
    Licence
    MIT

    Notice

    « tuning-hyperparameters » (Jeremy Longshore <jeremy@intentsolutions.io>, MIT) livré dans sa version d'origine : fiche en français et en anglais par PalateKit.

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