visenger/awesome-mlops
A curated list of references for MLOps
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.
Stars
13,810
Forks
2,028
Language
—
License
—
Category
Last pushed
Nov 21, 2024
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/visenger/awesome-mlops"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
EthicalML/awesome-production-machine-learning
A curated list of awesome open source libraries to deploy, monitor, version and scale your...
donnemartin/awesome-aws
A curated list of awesome Amazon Web Services (AWS) libraries, open source repos, guides, blogs,...
kelvins/awesome-mlops
:sunglasses: A curated list of awesome MLOps tools
aporia-ai/mlops.toys
🎲 A curated list of MLOps projects, tools and resources
aws-samples/awesome-sagemaker
A curated list of references for Amazon SageMaker