Speaker

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Juliet Hougland

Data Scientist, Cloudera

Juliet is a Data Scientist at Cloudera, and contributor/committer/maintainer for the Sparkling Pandas project. Her commercial applications of data science include developing predictive maintenance models for oil & gas pipelines at Deep Signal, and designing/building a platform for real-time model application, data storage, and model building at WibiData. Juliet was the technical editor for Learning Spark by Karau et al. and Advanced Analytics with Spark by Ryza et al. She holds an MS in Applied Mathematics from University of Colorado, Boulder and graduated Phi Beta Kappa from Reed College with a BA in Math-Physics.

Sessions

Best Practices for Running PySpark

PySpark (component of Spark allows users to write their code Python) has grabbed the attention of Python programmers who analyze and process data for a living. The appeal is obvious- you don’t need to learn…