Machine Learning for Email

Spam Filtering and Priority Inbox

Nonfiction, Computers, Database Management, Data Processing, General Computing, Programming
Cover of the book Machine Learning for Email by Drew Conway, John Myles White, O'Reilly Media
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Author: Drew Conway, John Myles White ISBN: 9781449320706
Publisher: O'Reilly Media Publication: October 25, 2011
Imprint: O'Reilly Media Language: English
Author: Drew Conway, John Myles White
ISBN: 9781449320706
Publisher: O'Reilly Media
Publication: October 25, 2011
Imprint: O'Reilly Media
Language: English

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
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

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.

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