ML Tasks, models, artifacts and datasets
Metrics tracking and visualization
Cost and performance tracking
OptScale integrates with Airflow, Jenkins, and GitHub Actions in MLOps to automate the end-to-end machine learning lifecycle.
With OptScale, users can orchestrate the ML workflow, schedule and manage model training jobs, ensuring that they run periodically or in response to specific triggers.
OptScale triggers the necessary jobs in the appropriate tools with the required parameters for various operations, such as training or retraining a model, deploying a model, generating a dataset, and more.
A full description of OptScale as an MLOps open source platform.
Enhance the ML process in your company with OptScale capabilities, including
Find out how to:
Powered by