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"I've built a model -- now what?"

Developing a predictive model is only one part of a larger journey. Data scientists have to access and transform data, and engineer features, before exploratory modeling happens. A model doesn't do anything until it's applied to data, productionised and deployed.


3 Things to Learn About:


  • How to uplevel your existing analytics stack with a collaborative environment that supports the latest open source languages and libraries.
  • How to get better use of your core data management investments while opening up new supported tools for data science.
  • How to expand data science outside of silo’d environments and enable self-service data science access.

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