visenger/awesome-mlops

A curated list of references for MLOps

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This is a curated collection of resources designed to help machine learning engineers, data scientists, and product managers effectively deploy and manage machine learning models in real-world applications. It provides links to articles, courses, books, and communities that explain how to take a trained machine learning model and integrate it into operational systems, ensuring reliability and continuous improvement. The goal is to provide a comprehensive guide for anyone looking to bridge the gap between developing ML models and running them successfully in production environments.

13,810 stars. No commits in the last 6 months.

Use this if you are a machine learning practitioner or manager looking for comprehensive resources to improve your understanding and implementation of MLOps practices.

Not ideal if you are a complete beginner to machine learning concepts and need an introduction to how models are built before considering their deployment.

MLOps Machine Learning Engineering Data Science Operations AI Product Management Model Deployment
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 10 / 25
Maturity 8 / 25
Community 22 / 25

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Last pushed

Nov 21, 2024

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