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Production deployment of machine learning models v1.0.0
Use this resource to deploy a machine learning model to production
New
- 552 downloads
- 120 likes
- 141 saves
Free
Install with the CLI
In a terminal, from the folder you want:
npx --yes palatekit@latest install ml-model-production-deploymentWith 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 analyses the requirement, generates the serving code and container files, adds input data validation and plans performance monitoring. It shows both a regression and a classification example. You get a deployment path and the matching service files.
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: deployment strategy, steps and best practices
- scripts/README.md and references/README.md: notes on scripts and references
Good fit for
- You need to expose a trained model through an API
- You want to containerise a model and track its performance in production
Not for
Tags
- machine learning
- deployment
- api
- container
About
You say
“Deploy my ticket classification model behind an API, in a container.”
Skill published by Jeremy Longshore <jeremy@intentsolutions.io> 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 deploy a machine learning model to production
- Review and adjust the result
Content preview
Files
- assets/README.md0.2 KB
- LICENSE1.1 KB
- NOTICE-PALATEKIT.md0.6 KB
- references/README.md0.1 KB
- scripts/README.md0.7 KB
- SKILL.md3.3 KB
Origin and licence
Listed unmodified
- Author
- Jeremy Longshore <jeremy@intentsolutions.io>
- Source
- github.com/jeremylongshore/tons-of-skills-marketplace/tree/ab85a061f7bcc039dac13ee193de7a4cd4388571/skills/.curated/deploying-machine-learning-models
- Licence
- MIT
Notice
« deploying-machine-learning-models » (Jeremy Longshore <jeremy@intentsolutions.io>, MIT) livré dans sa version d'origine : fiche en français et en anglais par PalateKit.
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