Best Practices for Succeeding with MLOps Webinar ft. Noah Gift author of 'Practical MLOps' - May 24th at 12pm ET
Consume MLRun, the scalable open source pipeline orchestration framework as a managed service in the Iguazio MLOps Platform. Leverage automation, scale and high performance to boost data workflow management, experiment tracking and reproducibility.
Run multiple experiments in parallel, each using a different combination of algorithm functions and parameter sets (hyper-parameters) to automatically select the best result.
Describe and track code, metadata, inputs and outputs of machine learning related tasks (executions) and re-use results with a generic and easy-to-use mechanism.
Maintain the same set of features in the training and inferencing (real-time) stages with MLRun’s unified feature store.
Natively integrate with Kubeflow Pipelines to compose, deploy and manage end-to-end machine learning workflows with UI and a set of services.
"Iguazio allowed us to unify and combine any data type to create real-time machine learning models with an out of the box data science toolkit. That to us was worth its weight in gold."
Director of DXP Innovation
"Iguazio provides us with an integrated platform which makes the job of better detecting fraud and ride usage much easier and efficient in the doing.”
Lead Data Scientist and Growth Hacker
“With Iguazio’s Data Science Platform, we built a scalable and reliable system which adapts to new threats and enables us to prevent fraud with minimum false positives”.
VP Corporate Security and Global IT Operations
Learn how you can automate, scale and orchestrate pipelines end to end with the Iguazio MLOps Platform