MLOps (Machine Learning Operations)

What is MLOps?

MLOps (Machine Learning Operations) is a critical function in Machine Learning engineering that optimizes the process of taking machine learning models to production and ensures their ongoing maintenance and monitoring.

MLOps facilitates collaboration between data scientists and machine learning engineers, accelerating model development and production through the implementation of continuous integration and deployment (CI/CD) practices. This approach includes proper monitoring, validation, and governance of ML models.

Adopting MLOps brings several benefits, including faster model development, the delivery of higher quality ML models, quicker deployment and production, and improved compliance with organizational or industry policies.

An MLOps platform automates operational and synchronization aspects of the machine learning lifecycle, providing a collaborative environment for data scientists and software engineers. This environment supports iterative data exploration, real-time co-working, experiment tracking, feature engineering, model management, controlled model transitioning, deployment, and monitoring.