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Machine Learning for Email by Drew Conway
Machine Learning for Email by Drew Conway
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Machine Learning for Email

Spam Filtering and Priority Inbox
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Description

This compact book explores standard tools for text classification, and teaches the reader how to use machine learning to decide whether a e-mail is spam or ham (binary classification), based on raw data from The SpamAssassin Public Corpus. Of course, sometimes the items in one class are not created equally, or we want to distinguish among them in some meaningful way. The second part of the book will look at how to not only filter spam from our email, but also placing "more important" messages at the top of the queue. This is a curated excerpt from the upcoming book "Machine Learning for Hackers."

Author Biography:

Drew Conway is a PhD candidate in Politics at NYU. He studies international relations, conflict, and terrorism using the tools of mathematics, statistics, and computer science in an attempt to gain a deeper understanding of these phenomena. His academic curiosity is informed by his years as an analyst in the U.S. intelligence and defense communities. John Myles White is a PhD candidate in Psychology at Princeton. He studies pattern recognition, decision-making, and economic behavior using behavioral methods and fMRI. He is particularly interested in anomalies of value assessment.
Release date Australia
December 6th, 2011
Author
Audience
  • Technical / Manuals
Pages
100
Dimensions
178x233x8
ISBN-13
9781449314309
Product ID
18634351

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Machine Learning for Hackers by Drew Conway
$126.99
Machine Learning for Hackers
by Drew Conway ~ Paperback / softback
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