Brainwashed: Building an IDE for Feature Engineering: Feature engineering- writing code to map raw input data into a set of signals that will be fed into a machine learning algorithm- is the dark art of data science. Although the process of crafting new features is tedious and failure-prone, the key to a successful model is a diverse set of high-quality features that are informed by domain experts. Recently, academic researchers have begun to focus on the problem of feature engineering, and have started to publish research that addresses the relative lack of tools that are designed to support the feature engineering process. In this talk, I will review some of my favorite papers and present some efforts to convert these ideas into tools that leverage the principles of reactive application design in order to make feature engineering (dare I say it) fun.

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Or, A Less Pretentious Title
Josh Wills | Senior Director of Data Science
Meditations on on
Feature Engineering

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About Me

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Data Scientists At Work

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Data Scientists at Home

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I For One…

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Deep Learning

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Deeper Deep Learning

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The Importance of Context

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Help Me Help You

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Brainwash!

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The Operational/Analytical Impedance Mismatch

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Supernova Schemas

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Exhibit: http://github.com/jwills/exhibit

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Demo Time!
jwills@cloudera.com