A Practical Introduction with Applications in R

Tree-Based Methods for Statistical Learning in R

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Praise for the Previous Edition
"The authors succeed in presenting the topics of number theory in a very easy and natural way, and the presence of interesting anecdotes, applications, and recent problems alongside the obvious mathematical rigor makes the book even more appealing. … a valid and flexible textbook for any undergraduate number theory course."—International Association for Cryptologic Research Book Reviews, May 2011
"… a welcome addition to the stable of elementary number theory works for all good undergraduate libraries."—J. McCleary, Vassar College,　Poughkeepsie, New York, USA, from CHOICE, Vol. 46, No. 1, August 2009　
"… a reader-friendly text. … provides all of the tools to achieve a solid foundation in number theory."—L’Enseignement Mathématique, Vol. 54, No. 2, 2008
The theory of numbers is a core subject of mathematics. The authors have written a solid update to the first edition (CH, Aug'09, 46-6857) of this classic topic. There is no shortage of introductions to number theory, and this book does not offer significantly different information. Nonetheless, the authors manage to give the subject a fresh, new feel. The writing style is simple, clear, and easy to follow for standard readers. The book contains all the essential topics of a first-semester course and enough advanced topics to fill a second. In particular, it includes several modern aspects of number theory, which are often ignored in other texts, such as the use of factoring in computer security, searching for large prime numbers, and connections to other branches of mathematics. Each section contains supplementary homework exercises of various difficulties, a crucial ingredient of any good textbook. Finally, much emphasis is placed on calculating with computers, a staple of modern number theory. Overall, this title should be considered by any student or professor seeking an excellent text on the subject.
--A. Misseldine, Southern Utah University, Choice magazine 2016

Introduction to Number Theory

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Tree-Based Methods for Statistical Learning in R

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