Presented By
O’Reilly + Cloudera
Make Data Work
March 25-28, 2019
San Francisco, CA
Till Bergmann

Till Bergmann
Senior Data Scientist, Salesforce

Till Bergmann is a senior data scientist at Salesforce Einstein, building platforms to make it easier to integrate machine learning into Salesforce products, with a focus on automating many of the laborious steps in the machine learning pipeline. He holds a PhD in cognitive science from the University of California, Merced, where he studied the collaboration patterns of academics using NLP techniques.

Sessions

2:40pm–3:20pm Thursday, March 28, 2019
How to train your model (and catch label leakage)
Data Science, Machine Learning & AI
 Location: 2010
Secondary topics:  AI and Data technologies in the cloud, AI and machine learning in the enterprise, Automation in data science and big data
Till Bergmann (Salesforce)
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A problem in predictive modeling data is label leakage. At enterprise companies such as Salesforce, this problem takes on monstrous proportions as the data is populated by diverse business processes, making it hard to distinguish cause from effect. Till Bergmann explains how Salesforce—which needs to churn out thousands of customer-specific models for any given use case—tackled this problem. Read more.