paiml/practical-mlops-book

[Book-2021] Practical MLOps O'Reilly Book

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This repository provides the code samples and practical examples from the O'Reilly book 'Practical MLOps.' It helps machine learning engineers and data scientists effectively deploy, monitor, and manage their machine learning models in production environments. You get hands-on code for various MLOps tasks, from model deployment strategies to monitoring, across major cloud platforms like AWS, Azure, and GCP.

942 stars. Actively maintained with 1 commit in the last 30 days.

Use this if you are an ML engineer or data scientist looking for practical, code-based guidance to implement robust MLOps practices for your machine learning projects.

Not ideal if you are looking for a conceptual overview of MLOps without any code, or if you prefer a non-technical introduction to machine learning.

MLOps Machine Learning Engineering Cloud Deployment Model Monitoring Continuous Delivery
No License No Package No Dependents
Maintenance 13 / 25
Adoption 10 / 25
Maturity 8 / 25
Community 25 / 25

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Last pushed

Feb 12, 2026

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