An easier way for data scientists to build reproducible experiments with machine learning pipelines and communicate operational dependencies to their engineering counterparts as part of a new MLOps approach you deploy to the Cloud and the Edge at scale. Chris Lauren the Principal Program Manager for the Azure Machine Learning Platform goes over the new Azure Machine Learning service. Chris shows you what capabilities data scientists can get across the machine learning lifecycle within a familiar notebook experience. And you'll see how you can use the newly introduced Automated Machine Learning capabilities in Azure ML to build machine learning models in a fraction of the time.
Was this article helpful?
That’s Great!
Thank you for your feedback
Sorry! We couldn't be helpful
Thank you for your feedback
Feedback sent
We appreciate your effort and will try to fix the article