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Friday, November 17 • 11:40am - 12:20pm
Fantastic ML apps and how to build them

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Building efficient machine learning applications is not a simple task. The typical engineering process is an iteration of data wrangling, feature generation, model selection, hyperparameter tuning and evaluation. The amount of possible variations of input features, algorithms and parameters makes it too complex to perform efficiently even by experts. Automating this process is especially important when building machine learning applications for thousands of customers. In this talk I demonstrate how we build effective ML models using AutoML capabilities we develop at Salesforce. Our AutoML capabilities include techniques for automatic data processing, feature generation, model selection, hyperparameter tuning and evaluation. I present several of the implemented solutions with Scala and Spark.

avatar for Matthew Tovbin

Matthew Tovbin

Principal Engineer, Salesforce Einstein, Salesforce
Matthew Tovbin is a Principal Member of Technical Staff at Salesforce, engineering Salesforce Einstein AI platform, which powers the world’s smartest CRM. Before joining Salesforce, he acted as a Director of Engineering at Badgeville, implementing scalable and highly available real-time... Read More →

Friday November 17, 2017 11:40am - 12:20pm PST