Tuesday, December 8, 2009, 11:27 AM
I learned of
"The Numerati" by Stephen Baker a couple of weeks ago in El Pais (a Spanish newspaper).
He signed the short story "Nos vigilan" (They are watching us) which depicts a scenario where "scientists" (mainly mathematicians and engineers) apply different tools and techniques in order to detect, track, and predict users behaviour under different situations (e.g. in the supermarket, during elections, when using the Internet, etc.)
The tone of the story is a bit Big-Brother-esque for my taste and, in my opinion, it fails in providing a realistic, albeit simplified, picture of the actual state of the art.
Because of that, I was reluctant to buy the book and, thus, I searched for some reviews on it.
This one, by Jeffrey Shallit, was pretty useful because it helped me to set my expectations towards the book which I, eventually, have bought and read.
After reading it, I must said that I mostly agree with Shallit's review: "The Numerati" is not a book for the technical savvy, and it probably also fails when introducing the field to the lay person. However, I haven't found it totally unenjoyable: despite the title and the short story in the newspaper, the book is not the mixture of Big Brother paranoia and Dan Brown I was afraid of. It (tries to) describe several fields where data mining and machine learning can be applied, the challenges researchers are finding, and the goals they try to reach.
All in all, I really recommend this book to those interested in data mining; hopefully, some of you could write a kind of version 2 of "The Numerati" providing a more accurate picture, while appealing to the general public at the same time.
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