Presented By
O’Reilly + Cloudera
Make Data Work
29 April–2 May 2019
London, UK
Eitan Anzenberg

Eitan Anzenberg
Director of Data Science, Bill.com

Website

Eitan is currently the Director of Data Science at Bill.com and has many years of experience as a scientist and researcher. His recent focus is in machine learning, deep learning, applied statistics and engineering. Before, Eitan was a Postdoctoral Scholar at Lawrence Berkeley National Lab, received his PhD in Physics from Boston University and his B.S. in Astrophysics from University of California Santa Cruz. Eitan has 2 patents and 11 publications to date and has spoken about data at various conferences around the world.

Sessions

14:5515:35 Wednesday, 1 May 2019
Data Science, Machine Learning & AI
Location: Capital Suite 15/16
Eitan Anzenberg (Bill.com)
Average rating: ****.
(4.50, 4 ratings)
Machine learning applications balance interpretability and performance. Linear models provide formulas to directly compare the influence of the input variables, while nonlinear algorithms produce more accurate models. Eitan Anzenberg explores a solution that utilizes what-if scenarios to calculate the marginal influence of features per prediction and compare with standardized methods such as LIME. Read more.