Playbook Data Science Ml To Prod

---
name: playbook-data-science-ml-to-prod
description: "Leakage-free validation and deployment-ready artifacts."
---
# Playbook: Take a model from notebook to production

> Leakage-free validation and deployment-ready artifacts.

**Track:** 🗺️ Data Science & Analytics · **Domain:** Journey Playbooks · **Level:** journey · **~60 min**

**Who this is for:** Data Scientists, Analysts, Research Scientists, Product Analysts

## When to Use This Skill

Leakage-free validation and deployment-ready artifacts.
Use it whenever a matching task appears in conversation — the agent loads these instructions on demand.

## Journey Steps

1. Step 1 — Baseline before you boost: start with "Predict the prior/majority class; record its metric as floor"
2. Step 2 — Prevent data leakage in ML pipelines: start with "Split temporally when production predicts the future"
3. How it fits together: Baselines price complexity. Leakage checks protect the offline-online gap that surprises everyone once.

### Referenced Skills

- `ml-modeling-baseline-first-modeling`
- `ml-modeling-leakage-prevention`

## Commands

**Install all referenced skills**
```bash
npx skills add aniruddhaadak80/skills --skill ml-modeling-baseline-first-modeling && npx skills add aniruddhaadak80/skills --skill ml-modeling-leakage-prevention
```

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Part of [aniruddhaadak80/skills](https://github.com/aniruddhaadak80/skills) · Browse all at https://skills.sh/aniruddhaadak80/skills