How Conexus Credit Union Uses Azure Machine Learning to Improve Business Processes
Watch the video in this article in order to learn more about what Conexus Credit Union is doing to improve business processes.
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Azure Machine Learning Studio is a collaborative, drag-and-drop tool you can use to build, test, and deploy predictive analytics solutions on your data. Conexus Credit Union, in a better way to serve their clients, wanted to find a way to help notify customers who were on the verge of defaulting on their financial responsibilities. By sifting through transactional data and using Azure Machine Learning, they were able to do just that.
Join Jerry Nixon as he welcomes Lauren Tran and Yvonne Hsieh from Microsoft and Clark Rensberry from Conexus Credit Union to the show as they share with us how they used Azure Machine Learning to help improve their customers financial health.
Short on time? Just click on any of the links below and jump to that section of the video:
- 0:04:26 --- How did Microsoft connect with Conexus Credit Union and what problem were they trying to solve?
- 0:08:43 –How do you make that initial decision where you knew ML was the way to go
- 0:10:12 – Let’s say we’re “feature engineering” --- what kind of features would we find for a project like this?
- 0:13:30 – What are the first steps in getting started with a project like this? How would a developer get started?
- 0:19:45 – DEMO: Azure Machine Learning Studio overview
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