MLOps - Machine Learning Operations & Production ML

MLOps - Machine Learning Operations

MLOps (Machine Learning Operations) encompasses practices and tools for deploying, monitoring, and maintaining machine learning models in production. MLOps bridges the gap between data science and operations, ensuring ML models are reliable, scalable, and maintainable.

MLOps applies DevOps principles to machine learning, focusing on automating and streamlining the ML lifecycle from development to deployment and monitoring.

Testing models for accuracy, performance, and reliability before deplo

Deploying models to production environments with proper infrastructure and monitoring.

Continuously monitoring model performance and system health in production.

Ensuring experiments and models can be reproduced by versioning code,

Automating repetitive tasks like training, testing, and deployment.

Implementing comprehensive monitoring for models, data, and infrastructure.

Frequently asked questions