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Machine Learning for Email
book

Machine Learning for Email

by Drew Conway, John Myles White
October 2011
Intermediate to advanced
142 pages
4h 15m
English
O'Reilly Media, Inc.
Content preview from Machine Learning for Email

Works Cited

Books

[Adl10] Joseph Adler. R in a Nutshell. O’Reilly Media. 2010.

[GH06] Andrew Gelman and Jennifer Hill. Data Analysis Using Regression and Multilevel/Hierarchical Models. Cambridge University Press. 2006.

[HTF09] Trevor Hastie, Robert Tibshirani, and Jerome Friedman. The Elements of Statistical Learning. Springer. 2009.

[JMR09] Owen Jones, Robert Maillardet, and Andrew Robinson. Introduction to Scientific Programming and Simulation Using R. Chapman and Hall. 2009.

[Pea09] Judea Pearl. Causality. Cambridge University Press. 2009.

[Seg07] Toby Segaran. Programming Collective Intelligence: Building Smart Web 2.0 Applications. O’Reilly Media. 2007.

[Spe08] Phil Spector. Data Manipulation with R. Springer. 2008.

[Wic09] Hadley Wickham. ggplot2: Elegant Graphics for Data Analysis. Springer. 2009.

[Wil05] Leland Wilkinson. The Grammar of Graphics. Springer. 2005.

Articles

[DA10] Douglas Aberdeen, Ondrej Pacovsky, and Andrew Slater. The Learning Behind Gmail Priority Inbox. LCCC : NIPS 2010 Workshop on Learning on Cores, Clusters and Clouds. http://research.google.com/pubs/archive/36955.pdf. 2010.

[HW11] Hadley Wickham. The Split-Apply-Combine Strategy for Data Analysis. Journal of Statistical Software. April, 2011. 40. 1.

[LF08] Uwe Ligges and John Fox. R help desk: How can I avoid this loop or make it faster?. http://www.r-project.org/doc/Rnews/Rnews_2008-1.pdf. May 2008.

[SR08] Randall Stross. What Has Driven Women Out of Computer Science?. The New York Times. November 15, ...

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Publisher Resources

ISBN: 9781449314835Errata Page