Salesforce powers a wide variety applications, many of which rely on custom predictions specified by end users—for example, companies predicting customer churn, college prep programs wanting to know the likelihood of students to enroll in college, and brands wanting to know how well their marketing campaigns are working and how to better target their efforts, to name just a few. These user-defined predictions require models automatically customized to each company’s dataset and use case.
Kevin Moore walks you through how TransmogrifAI—Salesforce’s open source AutoML library built on Spark—automatically generates these models and provides insights into why the model is making the predictions it does.
Kevin Moore is a senior data scientist at Salesforce, where he works on automated machine learning pipelines to generate and deploy customized models for a wide variety of customers and use cases. He holds a PhD in astrophysics and previously worked on modeling how stars evolve and eventually explode. When not stirring piles of linear algebra, he can usually be found snowboarding, brewing beer, or gaming.
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