MLOps in the Enterprise

Abstract: 

Learn how to bring ML to production and advance through the end to end ML lifecycle. We will review the customer maturity model for MLOps, its fundamental components. We will also show how we can use a CI (Continuous integration) approach to the data science workflow to automating the training and model testing process and use CD (Continuous Deployment) to automate the testing and deployment of production-ready models.

Bio: 

Abe Omorogbe is a Program Manager at Microsoft. He works within the AI Platform Group specifically on Azure Machine Learning - building exciting Machine Learning tools that make Data Scientist and ML Engineers more productive.

Open Data Science

 

 

 

Open Data Science
One Broadway
Cambridge, MA 02142
info@odsc.com

Privacy Settings
We use cookies to enhance your experience while using our website. If you are using our Services via a browser you can restrict, block or remove cookies through your web browser settings. We also use content and scripts from third parties that may use tracking technologies. You can selectively provide your consent below to allow such third party embeds. For complete information about the cookies we use, data we collect and how we process them, please check our Privacy Policy
Youtube
Consent to display content from - Youtube
Vimeo
Consent to display content from - Vimeo
Google Maps
Consent to display content from - Google