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Unmatched 50 Years of Supercomputing

Unmatched: 50 Years of Supercomputing: A Personal Journey Accompanying the Evolution of a Powerful Tool The rapid and extraordinary progress of supercomputing over the past half-century is a powerful demonstration of our relentless drive to understand and shape the world around us. In this book David Barkai offers a unique and compelling account of this remarkable technological journey drawing from his own rich experiences working at the forefront of high-performance computing (HPC). This book is a journey delineated as five decade-long ‘epochs’ defined by the systems’ architectural themes: vector processors multi-processors microprocessors clusters and accelerators and cloud computing. The final part examines key issues of HPC and discusses where it might be headed. A central goal of this book is to show how computing power has been applied and more importantly how it has impacted and benefitted society. To this end the use of HPC is illustrated in a range of industries and applications from weather and climate modeling to engineering and life sciences. As such this book appeals to both students and general readers with an interest in HPC as well as industry professionals looking to revolutionize their practice. From the Foreword: “David Barkai's career has spanned five decades during which he has had the rare opportunity to be part of some of the most significant developments in the field of supercomputing. His personal and professional insights combined with his deep knowledge and passion for the subject matter make this book an invaluable resource for anyone interested in the evolution of HPC and its impact on our lives. ” -Horst Simon Director Abu Dhabi Investment Authority (ADIA) Lab | Unmatched 50 Years of Supercomputing

GBP 45.99

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Algebraic Number Theory and Fermat's Last Theorem

Updated to reflect current research Algebraic Number Theory and Fermat’s Last Theorem Fourth Edition introduces fundamental ideas of algebraic numbers and explores one of the most intriguing stories in the history of mathematics—the quest for a proof of Fermat’s Last Theorem. The authors use this celebrated theorem to motivate a general study of the theory of algebraic numbers from a relatively concrete point of view. Students will see how Wiles’s proof of Fermat’s Last Theorem opened many new areas for future work. New to the Fourth EditionProvides up-to-date information on unique prime factorization for real quadratic number fields especially Harper’s proof that Z(√14) is EuclideanPresents an important new result: Mihăilescu’s proof of the Catalan conjecture of 1844Revises and expands one chapter into two covering classical ideas about modular functions and highlighting the new ideas of Frey Wiles and others that led to the long-sought proof of Fermat’s Last TheoremImproves and updates the index figures bibliography further reading list and historical remarksWritten by preeminent mathematicians Ian Stewart and David Tall this text continues to teach students how to extend properties of natural numbers to more general number structures including algebraic number fields and their rings of algebraic integers. It also explains how basic notions from the theory of algebraic numbers can be used to solve problems in number theory. | Algebraic Number Theory and Fermat's Last Theorem

GBP 39.99

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Exploratory Data Analysis with MATLAB

Praise for the Second Edition:The authors present an intuitive and easy-to-read book. … accompanied by many examples proposed exercises good references and comprehensive appendices that initiate the reader unfamiliar with MATLAB. —Adolfo Alvarez Pinto International Statistical Review Practitioners of EDA who use MATLAB will want a copy of this book. … The authors have done a great service by bringing together so many EDA routines but their main accomplishment in this dynamic text is providing the understanding and tools to do EDA. —David A Huckaby MAA Reviews Exploratory Data Analysis (EDA) is an important part of the data analysis process. The methods presented in this text are ones that should be in the toolkit of every data scientist. As computational sophistication has increased and data sets have grown in size and complexity EDA has become an even more important process for visualizing and summarizing data before making assumptions to generate hypotheses and models. Exploratory Data Analysis with MATLAB Third Edition presents EDA methods from a computational perspective and uses numerous examples and applications to show how the methods are used in practice. The authors use MATLAB code pseudo-code and algorithm descriptions to illustrate the concepts. The MATLAB code for examples data sets and the EDA Toolbox are available for download on the book’s website. New to the Third Edition Random projections and estimating local intrinsic dimensionality Deep learning autoencoders and stochastic neighbor embedding Minimum spanning tree and additional cluster validity indices Kernel density estimation Plots for visualizing data distributions such as beanplots and violin plots A chapter on visualizing categorical data

GBP 44.99

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Engineering Production-Grade Shiny Apps

From the Reviews [This book] contains an excellent blend of both Shiny-specific topics … and practical advice from software development that fits in nicely with Shiny apps. You will find many nuggets of wisdom sprinkled throughout these chapters…. Eric Nantz Host of the R-Podcast and the Shiny Developer Series (from the Foreword) [This] book is a gradual and pleasant invitation to the production-ready shiny apps world. It …exposes a comprehensive and robust workflow powered by the {golem} package. [It] fills the not yet covered gap between shiny app development and deployment in such a thrilling way that it may be read in one sitting…. In the industry world where processes robustness is a key toward productivity this book will indubitably have a tremendous impact. David Granjon Sr. Expert Data Science Novartis Presented in full color Engineering Production-Grade Shiny Apps helps people build production-grade shiny applications by providing advice tools and a methodology to work on web applications with R. This book starts with an overview of the challenges which arise from any big web application project: organizing work thinking about the user interface the challenges of teamwork and the production environment. Then it moves to a step-by-step methodology that goes from the idea to the end application. Each part of this process will cover in detail a series of tools and methods to use while building production-ready shiny applications. Finally the book will end with a series of approaches and advice about optimizations for production. Features Focused on practical matters: This book does not cover Shiny concepts but practical tools and methodologies to use for production. Based on experience: This book is a formalization of several years of experience building Shiny applications. Original content: This book presents new methodologies and tooling not just a review of what already exists. Engineering Production-Grade Shiny Apps covers medium to advanced content about Shiny so it will help people that are already familiar with building apps with Shiny and who want to go one step further.

GBP 48.99

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Promoting Statistical Practice and Collaboration in Developing Countries

Rarely but just often enough to rebuild hope something happens to confound my pessimism about the recent unprecedented happenings in the world. This book is the most recent instance and I think that all its readers will join me in rejoicing at the good it seeks to do. It is an example of the kind of international comity and collaboration that we could and should undertake to solve various societal problems. This book is a beautiful example of the power of the possible. [It] provides a blueprint for how the LISA 2020 model can be replicated in other fields. Civil engineers or accountants or nurses or any other profession could follow this outline to share expertise and build capacity and promote progress in other countries. It also contains some tutorials for statistical literacy across several fields. The details would change of course but ideas are durable and the generalizations seem pretty straightforward. This book shows every other profession where and how to stand in order to move the world. I urge every researcher to get a copy! —David Banks from the Foreword Promoting Statistical Practice and Collaboration in Developing Countries provides new insights into the current issues and opportunities in international statistics education statistical consulting and collaboration particularly in developing countries around the world. The book addresses the topics discussed in individual chapters from the perspectives of the historical context the present state and future directions of statistical training and practice so that readers may fully understand the challenges and opportunities in the field of statistics and data science especially in developing countries. Features • Reference point on statistical practice in developing countries for researchers scholars students and practitioners • Comprehensive source of state-of-the-art knowledge on creating statistical collaboration laboratories within the field of data science and statistics • Collection of innovative statistical teaching and learning techniques in developing countries Each chapter consists of independent case study contributions on a particular theme that are developed with a common structure and format. The common goal across the chapters is to enhance the exchange of diverse educational and action-oriented information among our intended audiences which include practitioners researchers students and statistics educators in developing countries.

GBP 105.00

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Probability and Statistics for Computer Scientists

Praise for the Second Edition: The author has done his homework on the statistical tools needed for the particular challenges computer scientists encounter. [He] has taken great care to select examples that are interesting and practical for computer scientists. . The content is illustrated with numerous figures and concludes with appendices and an index. The book is erudite and … could work well as a required text for an advanced undergraduate or graduate course. Computing Reviews Probability and Statistics for Computer Scientists Third Edition helps students understand fundamental concepts of Probability and Statistics general methods of stochastic modeling simulation queuing and statistical data analysis; make optimal decisions under uncertainty; model and evaluate computer systems; and prepare for advanced probability-based courses. Written in a lively style with simple language and now including R as well as MATLAB this classroom-tested book can be used for one- or two-semester courses. Features: Axiomatic introduction of probability Expanded coverage of statistical inference and data analysis including estimation and testing Bayesian approach multivariate regression chi-square tests for independence and goodness of fit nonparametric statistics and bootstrap Numerous motivating examples and exercises including computer projects Fully annotated R codes in parallel to MATLAB Applications in computer science software engineering telecommunications and related areas In-Depth yet Accessible Treatment of Computer Science-Related TopicsStarting with the fundamentals of probability the text takes students through topics heavily featured in modern computer science computer engineering software engineering and associated fields such as computer simulations Monte Carlo methods stochastic processes Markov chains queuing theory statistical inference and regression. It also meets the requirements of the Accreditation Board for Engineering and Technology (ABET). About the Author Michael Baron is David Carroll Professor of Mathematics and Statistics at American University in Washington D. C. He conducts research in sequential analysis and optimal stopping change-point detection Bayesian inference and applications of statistics in epidemiology clinical trials semiconductor manufacturing and other fields. M. Baron is a Fellow of the American Statistical Association and a recipient of the Abraham Wald Prize for the best paper in Sequential Analysis and the Regents Outstanding Teaching Award. M. Baron holds a Ph. D. in statistics from the University of Maryland. In his turn he supervised twelve doctoral students mostly employed on academic and research positions.

GBP 99.99

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Introduction to Proteins Structure Function and Motion Second Edition

Introduction to Proteins provides a comprehensive and state-of-the-art introduction to the structure function and motion of proteins for students faculty and researchers at all levels. The book covers proteins and enzymes across a wide range of contexts and applications including medical disorders drugs toxins chemical warfare and animal behavior. Each chapter includes a Summary Exercises and References. New features in the thoroughly-updated second edition include: A brand-new chapter on enzymatic catalysis describing enzyme biochemistry classification kinetics thermodynamics mechanisms and applications in medicine and other industries. These are accompanied by multiple animations of biochemical reactions and mechanisms accessible via embedded QR codes (which can be viewed by smartphones) An in-depth discussion of G-protein-coupled receptors (GPCRs) A wider-scale description of biochemical and biophysical methods for studying proteins including fully accessible internet-based resources such as databases and algorithms Animations of protein dynamics and conformational changes accessible via embedded QR codes Additional features Extensive discussion of the energetics of protein folding stability and interactions A comprehensive view of membrane proteins with emphasis on structure-function relationship Coverage of intrinsically unstructured proteins providing a complete realistic view of the proteome and its underlying functions Exploration of industrial applications of protein engineering and rational drug design Each chapter includes a Summary Exercies and References Approximately 300 color images Downloadable solutions manual available at www. crcpress. com For more information including all presentations tables animations and exercises as well as a complete teaching course on proteins' structure and function please visit the author's website. Praise for the first edition This book captures in a very accessible way a growing body of literature on the structure function and motion of proteins. This is a superb publication that would be very useful to undergraduates graduate students postdoctoral researchers and instructors involved in structural biology or biophysics courses or in research on protein structure-function relationships. David Sheehan ChemBioChem 2011 Introduction to Proteins is an excellent state-of-the-art choice for students faculty or researchers needing a monograph on protein structure. This is an immensely informative thoroughly researched up-to-date text with broad coverage and remarkable depth. Introduction to Proteins would provide an excellent basis for an upper-level or graduate course on protein structure and a valuable addition to the libraries of professionals interested in this centrally important field. Eric Martz Biochemistry and Molecular Biology Education 2012 | Introduction to Proteins Structure Function and Motion Second Edition

GBP 84.99

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A First Course in Machine Learning

A First Course in Machine Learning by Simon Rogers and Mark Girolami is the best introductory book for ML currently available. It combines rigor and precision with accessibility starts from a detailed explanation of the basic foundations of Bayesian analysis in the simplest of settings and goes all the way to the frontiers of the subject such as infinite mixture models GPs and MCMC. —Devdatt Dubhashi Professor Department of Computer Science and Engineering Chalmers University Sweden This textbook manages to be easier to read than other comparable books in the subject while retaining all the rigorous treatment needed. The new chapters put it at the forefront of the field by covering topics that have become mainstream in machine learning over the last decade. —Daniel Barbara George Mason University Fairfax Virginia USA The new edition of A First Course in Machine Learning by Rogers and Girolami is an excellent introduction to the use of statistical methods in machine learning. The book introduces concepts such as mathematical modeling inference and prediction providing ‘just in time’ the essential background on linear algebra calculus and probability theory that the reader needs to understand these concepts. —Daniel Ortiz-Arroyo Associate Professor Aalborg University Esbjerg Denmark I was impressed by how closely the material aligns with the needs of an introductory course on machine learning which is its greatest strength…Overall this is a pragmatic and helpful book which is well-aligned to the needs of an introductory course and one that I will be looking at for my own students in coming months. —David Clifton University of Oxford UK The first edition of this book was already an excellent introductory text on machine learning for an advanced undergraduate or taught masters level course or indeed for anybody who wants to learn about an interesting and important field of computer science. The additional chapters of advanced material on Gaussian process MCMC and mixture modeling provide an ideal basis for practical projects without disturbing the very clear and readable exposition of the basics contained in the first part of the book. —Gavin Cawley Senior Lecturer School of Computing Sciences University of East Anglia UK This book could be used for junior/senior undergraduate students or first-year graduate students as well as individuals who want to explore the field of machine learning…The book introduces not only the concepts but the underlying ideas on algorithm implementation from a critical thinking perspective. —Guangzhi Qu Oakland University Rochester Michigan USA

GBP 39.99

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Statistics in Engineering With Examples in MATLAB and R Second Edition

Engineers are expected to design structures and machines that can operate in challenging and volatile environments while allowing for variation in materials and noise in measurements and signals. Statistics in Engineering Second Edition: With Examples in MATLAB and R covers the fundamentals of probability and statistics and explains how to use these basic techniques to estimate and model random variation in the context of engineering analysis and design in all types of environments. The first eight chapters cover probability and probability distributions graphical displays of data and descriptive statistics combinations of random variables and propagation of error statistical inference bivariate distributions and correlation linear regression on a single predictor variable and the measurement error model. This leads to chapters including multiple regression; comparisons of several means and split-plot designs together with analysis of variance; probability models; and sampling strategies. Distinctive features include: All examples based on work in industry consulting to industry and research for industry Examples and case studies include all engineering disciplinesEmphasis on probabilistic modeling including decision trees Markov chains and processes and structure functionsIntuitive explanations are followed by succinct mathematical justificationsEmphasis on random number generation that is used for stochastic simulations of engineering systems demonstration of key concepts and implementation of bootstrap methods for inferenceUse of MATLAB and the open source software R both of which have an extensive range of statistical functions for standard analyses and also enable programing of specific applicationsUse of multiple regression for times series models and analysis of factorial and central composite designs Inclusion of topics such as Weibull analysis of failure times and split-plot designs that are commonly used in industry but are not usually included in introductory textbooksExperiments designed to show fundamental concepts that have been tested with large classes working in small groupsWebsite with additional materials that is regularly updatedAndrew Metcalfe David Green Andrew Smith and Jonathan Tuke have taught probability and statistics to students of engineering at the University of Adelaide for many years and have substantial industry experience. Their current research includes applications to water resources engineering mining and telecommunications. Mahayaudin Mansor worked in banking and insurance before teaching statistics and business mathematics at the Universiti Tun Abdul Razak Malaysia and is currently a researcher specializing in data analytics and quantitative research in the Health Economics and Social Policy Research Group at the Australian Centre for Precision Health University of South Australia. Tony Greenfield formerly Head of Process Computing and Statistics at the British Iron and Steel Research Association is a statistical consultant. He has been awarded the Chambers Medal for outstanding services to the Royal Statistical Society; the George Box Medal by the European Network for Business and Industrial Statistics for Outstanding Contributions to Industrial Statistics; and the William G. Hunter Award by the American Society for | Statistics in Engineering With Examples in MATLAB® and R Second Edition

GBP 44.99

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Games Gambling and Probability An Introduction to Mathematics

Many experiments have shown the human brain generally has very serious problems dealing with probability and chance. A greater understanding of probability can help develop the intuition necessary to approach risk with the ability to make more informed (and better) decisions. The first four chapters offer the standard content for an introductory probability course albeit presented in a much different way and order. The chapters afterward include some discussion of different games different ideas that relate to the law of large numbers and many more mathematical topics not typically seen in such a book. The use of games is meant to make the book (and course) feel like fun! Since many of the early games discussed are casino games the study of those games along with an understanding of the material in later chapters should remind you that gambling is a bad idea; you should think of placing bets in a casino as paying for entertainment. Winning can obviously be a fun reward but should not ever be expected. Changes for the Second Edition: New chapter on Game Theory New chapter on Sports Mathematics The chapter on Blackjack which was Chapter 4 in the first edition appears later in the book. Reorganization has been done to improve the flow of topics and learning. New sections on Arkham Horror Uno and Scrabble have been added. Even more exercises were added! The goal for this textbook is to complement the inquiry-based learning movement. In my mind concepts and ideas will stick with the reader more when they are motivated in an interesting way. Here we use questions about various games (not just casino games) to motivate the mathematics and I would say that the writing emphasizes a just-in-time mathematics approach. Topics are presented mathematically as questions about the games themselves are posed. Table of Contents Preface1. Mathematics and Probability 2. Roulette and Craps: Expected Value 3. Counting: Poker Hands 4. More Dice: Counting and Combinations and Statistics 5. Game Theory: Poker Bluffing and Other Games 6. Probability/Stochastic Matrices: Board Game Movement 7. Sports Mathematics: Probability Meets Athletics 8. Blackjack: Previous Methods Revisited 9. A Mix of Other Games 10. Betting Systems: Can You Beat the System? 11. Potpourri: Assorted Adventures in Probability Appendices Tables Answers and Selected Solutions Bibliography Biography Dr. David G. Taylor is a professor of mathematics and an associate dean for academic affairs at Roanoke College in southwest Virginia. He attended Lebanon Valley College for his B. S. in computer science and mathematics and went to the University of Virginia for his Ph. D. While his graduate school focus was on studying infinite dimensional Lie algebras he started studying the mathematics of various games in order to have a more undergraduate-friendly research agenda. Work done with two Roanoke College students Heather Cook and Jonathan Marino appears in this book! Currently he owns over 100 different board games and enjoys using probability in his decision-making while playing most of those games. In his spare time he enjoys reading cooking coding playing his board games and spending time with his six-year-old dog Lilly. | Games Gambling and Probability An Introduction to Mathematics

GBP 82.99

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