# Recommender system (/ml--recommender-system)

/ml--recommender-system is a Claude Code skill in the AI & Agents section. Builds a recommender that beats a popularity baseline: picks the approach, handles cold start and evaluates it offline.

- Web version: https://skills.sgomez.dev/en/s/ml--recommender-system
- 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/recommender-system.md
- Updated 10 Jul 2026

## How to ask for it

- `/ml--recommender-system design a product recommender for my store`
- `/ml--recommender-system handle cold start for new users`
- `/ml--recommender-system compare collaborative vs. hybrid approaches`

## 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`
- Network: No
- Destructive: No

## Author's description

Build a recommender: collaborative/content/hybrid choice, cold start, evaluation

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