# 02 - ML Pipelines with CI/CD: GitHub Actions and Docker

Complete guide to ML Pipelines with CI/CD: GitHub Actions and Docker: architecture, practical implementation and best practices for developers and technical teams.

## What you'll learn

- The Three ML Artifacts
- Continuous Training: The Key Concept
- Base Images for ML
- Multi-Stage Dockerfile for Training and Serving
- Layer Cache Optimization

*This article is part of the **MLOps** series on federicocalo.dev.*

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## Read the full article

The complete article (17 min read) with code examples, diagrams, and practical exercises is available here:

**➡️ [02 - ML Pipelines with CI/CD: GitHub Actions and Docker](https://federicocalo.dev/en/blog/ml-pipelines-cicd-github-actions-docker)**

`https://federicocalo.dev/en/blog/ml-pipelines-cicd-github-actions-docker`

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*By [Federico Calò](https://federicocalo.dev) — Software Developer & Technical Writer*