The Jupyter Workspaces beta capability in Domo provides a great way to explore your data in R or Python. As part of our general availability release, we are excited about multiple major enhancements to Domo Jupyter Workspaces. These include scheduled notebook executions, customizable Conda environments and a persistent file system. During this session, Joe Clark from Domo will show how these improvements can be used to create end-to-end data science or ML pipelines.
In this session you’ll learn:
Basic Jupyter functionality
How schedule notebook executions can transform the data science experience in Domo
And other improvements to Domo Jupyter Workspaces
Joe Clark, Software Architect – Labs at Domo, Domo