mlops-course and MLprod

The two tools are competitors, as both repositories provide course materials and resources aiming to teach the principles and practices of Machine Learning in production environments.

mlops-course
50
Established
MLprod
40
Emerging
Maintenance 0/25
Adoption 10/25
Maturity 16/25
Community 24/25
Maintenance 10/25
Adoption 4/25
Maturity 16/25
Community 10/25
Stars: 3,316
Forks: 592
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License: MIT
Stars: 6
Forks: 1
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License: MIT
Stale 6m No Package No Dependents
No Package No Dependents

About mlops-course

GokuMohandas/mlops-course

Learn how to design, develop, deploy and iterate on production-grade ML applications.

This course teaches you how to build, deploy, and continuously improve machine learning applications for real-world use. It guides you from initial model development and experimentation to creating robust, production-ready systems. The course takes in raw data and model designs and outputs deployable, scalable machine learning services, designed for software engineers, data scientists, and technical leaders working with ML.

MLOps Machine Learning Engineering Production AI Data Science Workflow Model Deployment

About MLprod

IDSIA/MLprod

Machine Learning in Production

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