InfoQ Homepage Presentations Predictability in ML Applications
Predictability in ML Applications
Summary
Claudia Perlich presents a number of scenarios in which the combination of different and highly informative features can have significantly negative overall impact on the usefulness of predictive modeling.
Bio
Claudia Perlich currently acts as Chief Scientist at Distillery (previously m6d), and in this role designs, develops, analyzes, and optimizes the machine learning that drives digital advertising. She has published more than 50 scientific articles and holds multiple patents in machine learning.
About the conference
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