# Ml Pipeline Workflow

> Build end-to-end MLOps pipelines from data preparation through model training, validation, and production deployment. Use when creating ML pipelines, implementing MLOps practices, or automating model training and deployment workflows.

- Skill: `dokhacgiakhoa/ml-pipeline-workflow` (Agent Skill, multi-file: 18 files)
- Install (CLI): `npx skillmds@latest add dokhacgiakhoa/ml-pipeline-workflow`
- Raw SKILL.md: https://api.skillmd.com/api/skills/dokhacgiakhoa/ml-pipeline-workflow/raw
- Safety review: pending (external: skill-scanner PASS, skillspector PASS)
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: DevOps & Infra
- Author: Dokhacgiakhoa (https://skillmd.com/u/dokhacgiakhoa)
- Updated: 2026-09-09
- Page: https://skillmd.com/skills/dokhacgiakhoa/ml-pipeline-workflow

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# ML Pipeline Workflow

Complete end-to-end MLOps pipeline orchestration from data preparation through model deployment.

## Do not use this skill when

- The task is unrelated to ml pipeline workflow
- You need a different domain or tool outside this scope

## Instructions

- Clarify goals, constraints, and required inputs.
- Apply relevant best practices and validate outcomes.
- Provide actionable steps and verification.
- If detailed examples are required, open `resources/implementation-playbook.md`.

## Overview

This skill provides comprehensive guidance for building production ML pipelines that handle the full lifecycle: data ingestion → preparation → training → validation → deployment → monitoring.

## Use this skill when

- Building new ML pipelines from scratch
- Designing workflow orchestration for ML systems
- Implementing data → model → deployment automation
- Setting up reproducible training workflows
- Creating DAG-based ML orchestration
- Integrating ML components into production systems

## What This Skill Provides

## 🧠 Knowledge Modules (Fractal Skills)

### 1. [Core Capabilities](./sub-skills/core-capabilities.md)
### 2. [Reference Documentation](./sub-skills/reference-documentation.md)
### 3. [Assets and Templates](./sub-skills/assets-and-templates.md)
### 4. [Basic Pipeline Setup](./sub-skills/basic-pipeline-setup.md)
### 5. [Production Workflow](./sub-skills/production-workflow.md)
### 6. [Pipeline Design](./sub-skills/pipeline-design.md)
### 7. [Data Management](./sub-skills/data-management.md)
### 8. [Model Operations](./sub-skills/model-operations.md)
### 9. [Deployment Strategies](./sub-skills/deployment-strategies.md)
### 10. [Orchestration Tools](./sub-skills/orchestration-tools.md)
### 11. [Experiment Tracking](./sub-skills/experiment-tracking.md)
### 12. [Deployment Platforms](./sub-skills/deployment-platforms.md)
### 13. [Batch Training Pipeline](./sub-skills/batch-training-pipeline.md)
### 14. [Real-time Feature Pipeline](./sub-skills/real-time-feature-pipeline.md)
### 15. [Continuous Training](./sub-skills/continuous-training.md)
### 16. [Common Issues](./sub-skills/common-issues.md)
### 17. [Debugging Steps](./sub-skills/debugging-steps.md)