Your teams have the flexibility to use the data science tools they already use (e.g. Jupyter, RStudio, SAS, MATLAB, Spark) and the distributed compute frameworks they need (e.g. Spark, Ray, Dask) in an integrated environment that eliminates distractions so they can focus on developing and deploying models.
You have the benefit of a single platform with holistic visibility and standardized processes so you get the information you need to manage teams and prioritize work more efficiently.
You can develop a culture of collaboration and continuous learning to drive an ever-increasing flow of business value.
If you don’t have the right infrastructure - you’re lost - we really needed a ML platform. You need a version of code running, who deployed what, and freedom to choose what open source tools they want. They’re free to do what they need to do, and they never have questions about Domino - because they just get on with it. Like playing a piano, or a violin.
Senior Project Manager, Machine Learning
Case Study: Giving Homeowners Answers About Insurance Coverage in Seconds with Model-driven Policy Approvals
Topdanmark’s model-driven policy approvals, powered by Domino, reduce the time to approve coverage from four days to one to two seconds.Read The Story
Estimate Your ROI from Domino
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