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Synopsis
If you're an experienced programmer willing to crunch data, this concise guide will show you how to use machine learning to work with email. You'll learn how to write algorithms that automatically sort and redirect email based on statistical patterns. Authors Drew Conway and John Myles White approach the process in a practical fashion, using a case-study driven approach rather than a traditional math-heavy presentation.
This book also includes a short tutorial on using the popular R language to manipulate and analyze data. You'll get clear examples for analyzing sample data and writing machine learning programs with R.
- Mine email content with R functions, using a collection of sample files
- Analyze the data and use the results to write a Bayesian spam classifier
- Rank email by importance, using factors such as thread activity
- Use your email ranking analysis to write a priority inbox program
- Test your classifier and priority inbox with a separate email sample set
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
À propos des auteurs
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 Ph.D. student in the Princeton Psychology Department, where he studies how humans make decisions both theoretically and experimentally. Outside of academia, John has been heavily involved in the data science movement, which has pushed for an open source software approach to data analysis. He is also the lead maintainer for several popular R packages, including ProjectTemplate and log4r.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Machine Learning for Email
Vendeur : PBShop.store US, Wood Dale, IL, Etats-Unis
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Machine Learning for Email: Spam Filtering and Priority Inbox
Edité par
O'Reilly Media, 2011
ISBN 10 : 1449314309
ISBN 13 : 9781449314309
Ancien ou d'occasion
Paperback
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Paperback. Etat : Very Good. The book has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged. N° de réf. du vendeur GOR009374166
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Machine Learning for Email
Vendeur : PBShop.store UK, Fairford, GLOS, Royaume-Uni
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PAP. Etat : New. New Book. Shipped from UK. Established seller since 2000. N° de réf. du vendeur WO-9781449314309
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Machine Learning for Email: Spam Filtering and Priority Inbox
Edité par
O'Reilly Media, Inc, USA, 2011
ISBN 10 : 1449314309
ISBN 13 : 9781449314309
Neuf
Paperback / softback
Vendeur : THE SAINT BOOKSTORE, Southport, Royaume-Uni
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Paperback / softback. Etat : New. New copy - Usually dispatched within 4 working days. 275. N° de réf. du vendeur B9781449314309
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Machine Learning for Email
Vendeur : Rarewaves USA, OSWEGO, IL, Etats-Unis
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Paperback. Etat : New. 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.". N° de réf. du vendeur LU-9781449314309
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Machine Learning for Email: Spam Filtering and Priority Inbox
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Machine Learning for Email
Vendeur : Rarewaves USA United, OSWEGO, IL, Etats-Unis
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Paperback. Etat : New. 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.". N° de réf. du vendeur LU-9781449314309
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Machine Learning for Email
Vendeur : Kennys Bookshop and Art Galleries Ltd., Galway, GY, Irlande
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Etat : New. 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. . 2011. Paperback. . . . . N° de réf. du vendeur V9781449314309
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Conway, D: Machine Learning for Email
Vendeur : moluna, Greven, Allemagne
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Etat : New. 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.Über . N° de réf. du vendeur 595883649
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Machine Learning for Email: Spam Filtering and Priority Inbox
Vendeur : California Books, Miami, FL, Etats-Unis
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Etat : New. N° de réf. du vendeur I-9781449314309
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