Presented By O'Reilly and Cloudera
Make Data Work
September 25–26, 2017: Training
September 26–28, 2017: Tutorials & Conference
New York, NY
Jacob Schreiber

Jacob Schreiber
Graduate Student, University of Washington

Website

Jacob Schreiber is a third-year CSE PhD student and IGERT big data fellow at the University of Washington. Jacob is a core developer for the popular Python machine learning package sklearn and the author of a probabilistic modeling Python package pomegranate.

Sessions

Secondary topics:  Pydata
Jacob Schreiber (University of Washington)
Average rating: ****.
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Jacob Schreiber offers an overview of pomegranate, a flexible probabilistic modeling package implemented in Cython for speed. Jacob explores the models it supports, such as Bayesian networks and hidden Markov models, and how to easily implement them and explains how the underlying modular implementation unlocks several benefits for the modern data scientist. Read more.