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- Author: Drew Conway
- Publisher: O'Reilly Media
- ISBN-10: 1449314309
- ISBN-13: 9781449314309
- Format: 17.8 x 23.3 x 0.8 cm, softcover
- Language: English
- SAVE -10% with code: EXTRA
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Description
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
EXTRA 10 % discount with code: EXTRA
The promotion ends in 17d.16:00:04
The discount code is valid when purchasing from 10 €. Discounts do not stack.
- Author: Drew Conway
- Publisher: O'Reilly Media
- ISBN-10: 1449314309
- ISBN-13: 9781449314309
- Format: 17.8 x 23.3 x 0.8 cm, softcover
- Language: English 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
Reviews