Springer, 2012. — 753 p.
This book describes the key concepts, principles and implementation options for creating high-assurance cloud computing solutions. The guide starts with a broad technical overview and basic introduction to cloud computing, looking at the overall architecture of the cloud, client systems, the modern Internet and cloud computing data centers. It then...
Wiley, 2012. — 360 p.
This book provides an insight into the publish/subscribe technology including the design, implementation, and evaluation of new systems based on the technology. The book also addresses the basic design patterns and solutions, and discusses their application in practical application scenarios. Furthermore, the author examines current standards and industry...
No Starch Press, 2003. — 280 p. — ISBN 978-1886411951. This book finds and analyzes bugs in some broken programs and, thus, helps the reader become a better programmer. Based on real-world errors, the puzzles range from easy (one wrong character) to mind twisting (errors with multiple threads). Match your wits against the author's and polish your language skills as you try to...
2nd edition. — Springer, 2003. — 312 p. Measure, Integral and Probability is a gentle introduction that makes measure and integration theory accessible to the average third-year undergraduate student. The ideas are developed at an easy pace in a form that is suitable for self-study, with an emphasis on clear explanations and concrete examples rather than abstract theory. For...
2nd Edition. — Imperial College Press, 2005. — 412 p. The book is a mathematical text, but the entrance level is lower than other rigorous stochastic calculus books. It is is suitable for advanced undergraduates, graduates and researchers in probability & statistics and mathematical finance.
The MIT Press, 2010. — 632 p. This text offers an introduction to the core topics underlying modern search technologies, including algorithms, data structures, indexing, retrieval, and evaluation. The emphasis is on implementation and experimentation; each chapter includes exercises and suggestions for student projects.
Springer, 1985. — 617 p.
This book is very deep and will not just teach you theory and techniques but will teach you how to think and how to approach and formulate problems, as well as how to interpret the results obtained by various methods and use them in a practical setting. This book is very practically oriented.
Springer, 2008. — 741 p. This book is an encyclopedic treatment of classic as well as contemporary large sample theory, dealing with both statistical problems and probabilistic issues and tools. It is written in an extremely lucid style, with an emphasis on the conceptual discussion of the importance of a problem and the impact and relevance of the theorems.
John Wiley & Sons, 1986. — 938 p. This is the first book to summarize a broad cross-section of the large volume of literature available on one-dimensional empirical processes.
Springer, 2005. — 672 p. — ISBN: 0387402640, 978-0387402642.
This book is a comprehensive treatment of inference for hidden Markov models, including both algorithms and statistical theory. Topics range from filtering and smoothing of the hidden Markov chain to parameter estimation, Bayesian methods and estimation of the number of states. In a unified way the book covers both...
Springer, 2006. — 280 p. There are many books on various aspects of nonparametric inference such as density estimation, nonparametric regression, bootstrapping, and wavelets methods. But it is hard to find all these topics covered in one place. The goal of this text is to provide the reader with a single book where they can find a brief account of many of the modern topics in...
Wiley-Interscience, 2003. — 328 p. This book is specifically tailored to the introductory course on statistical distributions, this unmatched resource takes a more balanced, all-inclusive approach than similar texts. In page after page, you’ll find a valuable review of often-overlooked distributions, including geometric, negative binomial, hypergeometric, Pareto, beta, gamma,...
Springer, 1999. — 530 p. This book consists of four hundred exercises in mathematical statistics and their solutions. This book is for students preparing for work on a Ph.D. degree in statistics and instructors of mathematical statistics courses, this useful book provides solutions to train students for their research ability in mathematical statistics and presents many...
Springer, 2009. — 353 p. — (Springer Series in Statistics). — ISBN 978-0-387-92709-1. Comparing Distributions refers to the statistical data analysis that encompasses the traditional goodness-of-fit testing. Whereas the latter includes only formal statistical hypothesis tests for the one-sample and the K-sample problems, this book presents a more general and informative...
Cambridge University Press, 2005. — 236 p. This engaging textbook introduces the key ideas behind drawing formal inferences from data. Aimed at advanced undergraduates and graduate students in mathematics and related disciplines, it is a concise account of the main approaches to inference, with particular emphasis on the contrasts between them.
Springer, 2010. — 609 p. — (Springer Texts in Statistics). — ISBN 978-1-4419-6826-5. This book offers a comprehensive guide to large sample techniques in statistics. More importantly, it focuses on thinking skills rather than just what formulae to use; it provides motivations, and intuition, rather than detailed proofs; it begins with very simple techniques, and connects theory...