(This article was originally published at Three-Toed Sloth , and syndicated at StatsBlogs.)

Attention conservation notice:As though I don't drone on about technical books too much as it is, pointers to five reviews averaging 2,000+ words each.

Some notes on books which grew too large for the end-of-the-month wrap-ups:

- Robert E. Schapire and Yoav Freund, Boosting: Foundations and Algorithms
- D. R. Cox and Christl A. Donnelly, Principles of Applied Statistics
- Peter Bühlmann and Sara van de Geer, Statistics for High-Dimensional Data: Methods, Theory and Applications
- Cristopher Moore and Stephan Mertens, The Nature of Computation
- Mehryar Mohri, Afshin Rostamizadeh and Ameet Talwalkar, Foundations of Machine Learning

The review of Cox and Donnelly originally ran in American Scientist. The reviews of Moore and Mertens, and of Bühlmann and van de Geer, were things I started last year and only just finished.

Enigmas of Chance; Automata and Calculating Machines

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