FreeSkills
Commits, branches and sync with the but CLI
- 361361 downloads
- 198198 likes
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Works with
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- Codex
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Machine learning pipeline build v1.0.0
Use this resource to build a machine learning pipeline from data to a serving endpoint
New
- 600 downloads
- 142 likes
- 176 saves
Free
Install with the CLI
In a terminal, from the folder you want:
npx --yes palatekit@latest install ml-pipeline-buildWith 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 loginThe agent detects the project's ML stack, defines the success metric and first builds a simple baseline. It then adds data validation, features, the training script, evaluation, the serving endpoint and monitoring.
Mostly picked by
Updated November 2, 2026
Previews
Details
- Install guides
- Generates with
- Your agent's model
- Licence
- MIT
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What you get
- SKILL.md: steps from success metric to monitoring, from baseline to serving endpoint
- .claude-plugin/plugin.json: plugin metadata
Good fit for
- You want to train a first classification or regression model
- Your team must move from a notebook to a prediction service
Not for
Tags
- machine learning
- pipeline
- training
- evaluation
- serving
About
You say
“Build a pipeline that predicts customer churn, starting from a simple baseline.”
Skill published by tonone-ai <hello@tonone.ai> under the MIT license, delivered in its original version.
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How to use it
- Install the skill in your agent's skills folder
- Ask your agent to build a machine learning pipeline from data to a serving endpoint
- Review and adjust the result
Content preview
Files
- .claude-plugin/plugin.json0.5 KB
- LICENSE1.1 KB
- NOTICE-PALATEKIT.md0.5 KB
- SKILL.md4.9 KB
Origin and licence
Listed unmodified
- Author
- tonone-ai <hello@tonone.ai>
- Source
- github.com/jeremylongshore/tons-of-skills-marketplace/tree/ab85a061f7bcc039dac13ee193de7a4cd4388571/plugins/ai-agency/tonone/skills/cortex-model
- Licence
- MIT
Notice
« cortex-model » (tonone-ai <hello@tonone.ai>, MIT) livré dans sa version d'origine : fiche en français et en anglais par PalateKit.
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