Machine Learning in Production: Developing and Optimizing Data Science Workflows and Applications
by Andrew Kelleher, Adam Kelleher
Preface
Most of this book was written while Andrew and Adam were working together at BuzzFeed. Adam was a data scientist, Andrew was an engineer, and they spent a good deal of time working together on the same team! Given that they’re identical twins of triplets, it was confusing and amusing for everyone involved.
The idea for this book came after PyGotham in New York City in August 2014. There were several talks relating to the relatively broadly defined field of “data science.” What we noticed was that many data scientists start their careers driven by the curiosity and excitement of learning new things. They discover new tools and often have a favorite technique or algorithm. They’ll apply that tool to the problem they’re working on. When ...
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