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Machine Learning for Email
Drew Conway
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Description for Machine Learning for Email
Paperback. 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. Num Pages: 146 pages, Illustrations. BIC Classification: UMB; UYQM. Category: (XV) Technical / Manuals. Dimension: 234 x 179 x 9. Weight in Grams: 266.
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 ... Read more
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 ... Read more
Product Details
Format
Paperback
Publication date
2011
Publisher
O´Reilly Media United States
Number of pages
146
Condition
New
Number of Pages
100
Place of Publication
Sebastopol, United States
ISBN
9781449314309
SKU
V9781449314309
Shipping Time
Usually ships in 7 to 11 working days
Ref
99-1
About Drew Conway
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 ... Read more
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