# Deploying an ML model (/ml--model-deployment)

/ml--model-deployment is a Claude Code skill in the AI & Agents section. Takes a trained model to production: batch or online serving pattern, prediction API, packaging, monitoring, drift detection and rollback plan.

- Web version: https://skills.sgomez.dev/en/s/ml--model-deployment
- Section: [AI & Agents](https://skills.sgomez.dev/en/ai.md)
- Author: Santiago Gómez de la Torre
- License: MIT
- Source: https://github.com/sgomez-dev/claude-skills/blob/main/skills/ml/model-deployment.md
- Updated 10 Jul 2026

## How to ask for it

- `/ml--model-deployment deploy my model as an online API`
- `/ml--model-deployment set up batch inference for this model`
- `/ml--model-deployment add drift detection to my production model`

## Install

macOS · Linux:

```
curl -fsSL https://raw.githubusercontent.com/sgomez-dev/claude-skills/main/install.sh | bash
```

Windows:

```
irm https://raw.githubusercontent.com/sgomez-dev/claude-skills/main/install.ps1 | iex
```

Claude Code plugin:

```
/plugin marketplace add sgomez-dev/claude-skills
/plugin install ml-skills@claude-skills-collection
```

## Permissions

- Reads: `**/*`
- Writes: `**/*`
- Runs: `python`, `pip`, `docker`
- Network: No
- Destructive: No

## Author's description

Deploy an ML model: serving pattern (batch/online), API, monitoring, drift detection

- [How we review this](https://skills.sgomez.dev/en/methodology.md)