1Bookcase - 8 books ready for downloading |  |
- Principles of Data Mining, 2nd Edition
- Parallel Programming: for Multicore and Cluster Systems, 2nd Edition
- Markov Models for Pattern Recognition, 2nd Edition
- Learning C# by Programming Games
- Introduction to Partial Differential Equations
- High Energy Cosmic Rays, 2nd Edition
- Excel 2010 for Social Science Statistics
- Data Mining for Service
| Principles of Data Mining, 2nd Edition Posted: 20 Apr 2016 03:34 AM PDT  Principles of Data Mining (Undergraduate Topics in Computer Science), 2nd Edition.Data Mining, the automatic extraction of implicit and potentially useful information from data, is increasingly used in commercial, scientific and other application areas. Principles of Data Mining explains and explores the principal techniques of Data Mining: for classification, association rule mining and clustering. Each topic is clearly explained and illustrated by detailed worked examples, with a focus on algorithms rather than mathematical formalism. It is written for readers without a strong background in mathematics or statistics, and any formulae used are explained in detail. This second edition has been expanded to include additional chapters on using frequent pattern trees for Association Rule Mining, comparing classifiers, ensemble classification and dealing with very large volumes of data. Principles of Data Mining aims to help general readers develop the necessary understanding of what is inside the ‘black box’ so they can use commercial data mining packages discriminatingly, as well as enabling advanced readers or academic researchers to understand or contribute to future technical advances in the field. Suitable as a textbook to support courses at undergraduate or postgraduate levels in a wide range of subjects including Computer Science, Business Studies, Marketing, Artificial Intelligence, Bioinformatics and Forensic Science. The post Principles of Data Mining, 2nd Edition appeared first on 1Bookcase. |
| Parallel Programming: for Multicore and Cluster Systems, 2nd Edition Posted: 20 Apr 2016 03:26 AM PDT  Parallel Programming: for Multicore and Cluster Systems, 2nd Edition.Innovations in hardware architecture, like hyper-threading or multicore processors, mean that parallel computing resources are available for inexpensive desktop computers. In only a few years, many standard software products will be based on concepts of parallel programming implemented on such hardware, and the range of applications will be much broader than that of scientific computing, up to now the main application area for parallel computing. Rauber and Rünger take up these recent developments in processor architecture by giving detailed descriptions of parallel programming techniques that are necessary for developing efficient programs for multicore processors as well as for parallel cluster systems and supercomputers. Their book is structured in three main parts, covering all areas of parallel computing: the architecture of parallel systems, parallel programming models and environments, and the implementation of efficient application algorithms. The emphasis lies on parallel programming techniques needed for different architectures. For this second edition, all chapters have been carefully revised. The chapter on architecture of parallel systems has been updated considerably, with a greater emphasis on the architecture of multicore systems and adding new material on the latest developments in computer architecture. Lastly, a completely new chapter on general-purpose GPUs and the corresponding programming techniques has been added. The main goal of the book is to present parallel programming techniques that can be used in many situations for a broad range of application areas and which enable the reader to develop correct and efficient parallel programs. Many examples and exercises are provided to show how to apply the techniques. The book can be used as both a textbook for students and a reference book for professionals. The material presented has been used for courses in parallel programming at different universities for many years. The post Parallel Programming: for Multicore and Cluster Systems, 2nd Edition appeared first on 1Bookcase. |
| Markov Models for Pattern Recognition, 2nd Edition Posted: 20 Apr 2016 03:21 AM PDT  Markov Models for Pattern Recognition: From Theory to Applications (Advances in Computer Vision and Pattern Recognition), 2nd Edition.Markov models are extremely useful as a general, widely applicable tool for many areas in statistical pattern recognition. This unique text/reference places the formalism of Markov chain and hidden Markov models at the very center of its examination of current pattern recognition systems, demonstrating how the models can be used in a range of different applications. Thoroughly revised and expanded, this new edition now includes a more detailed treatment of the EM algorithm, a description of an efficient approximate Viterbi-training procedure, a theoretical derivation of the perplexity measure, and coverage of multi-pass decoding based on n-best search. Supporting the discussion of the theoretical foundations of Markov modeling, special emphasis is also placed on practical algorithmic solutions. Topics and features:
Researchers, practitioners, and graduate students of pattern recognition will all find this book to be invaluable in aiding their understanding of the application of statistical methods in this area. The post Markov Models for Pattern Recognition, 2nd Edition appeared first on 1Bookcase. |
| Learning C# by Programming Games Posted: 20 Apr 2016 03:14 AM PDT  Learning C# by Programming Games.C# is the language of choice for learning how to program. It is a very well structured object-oriented language and avoids some of the problems of Java. An excellent free programming environment is available for C#, as well as a game programming framework. And (if necessary) moving from C# to C++ is easy. Developing computer games is a perfect way to learn how to program in modern programming languages. This book teaches how to program in C# through the creation of computer games – and without requiring any previous programming experience. Contrary to most programming books, Egges, Fokker and Overmars do not organize the presentation according to programming language constructs, but instead use the structure and elements of computer games as a framework. For instance, there are chapters on dealing with player input, game objects, game worlds, game states, levels, animation, physics, and intelligence. The reader will be guided through the development of four games showing the various aspects of game development. Starting with a simple shooting game, the authors move on to puzzle games consisting of multiple levels, and conclude the book by developing a full-fledged platform game with animation, game physics, and intelligent enemies. They show a number of commonly used techniques in games, such as drawing layers of sprites, rotating, scaling and animating sprites, showing a heads-up display, dealing with physics, handling interaction between game objects, and creating pleasing visual effects such as snow or glitter. At the same time, they provide a thorough introduction to C# and object-oriented programming, introducing step by step important aspects of programming in general, including many programming constructs and idioms, syntax diagrams, collections, and exception handling. The book is also designed to be used as a basis for a game-oriented programming course. For each part, there are concluding exercises and challenges, which are generally more complex programming endeavors. Lots of supplementary materials for organizing such a course are available on the accompanying web site http://www.csharpprogramminggames.com, including installation instructions, solutions to the exercises, software installation instructions, game sprites and sounds. The post Learning C# by Programming Games appeared first on 1Bookcase. |
| Introduction to Partial Differential Equations Posted: 20 Apr 2016 03:08 AM PDT  Introduction to Partial Differential Equations (Undergraduate Texts in Mathematics).This textbook is designed for a one year course covering the fundamentals of partial differential equations, geared towards advanced undergraduates and beginning graduate students in mathematics, science, engineering, and elsewhere. The exposition carefully balances solution techniques, mathematical rigor, and significant applications, all illustrated by numerous examples. Extensive exercise sets appear at the end of almost every subsection, and include straightforward computational problems to develop and reinforce new techniques and results, details on theoretical developments and proofs, challenging projects both computational and conceptual, and supplementary material that motivates the student to delve further into the subject. No previous experience with the subject of partial differential equations or Fourier theory is assumed, the main prerequisites being undergraduate calculus, both one- and multi-variable, ordinary differential equations, and basic linear algebra. While the classical topics of separation of variables, Fourier analysis, boundary value problems, Green’s functions, and special functions continue to form the core of an introductory course, the inclusion of nonlinear equations, shock wave dynamics, symmetry and similarity, the Maximum Principle, financial models, dispersion and solitons, Huygens’ Principle, quantum mechanical systems, and more make this text well attuned to recent developments and trends in this active field of contemporary research. Numerical approximation schemes are an important component of any introductory course, and the text covers the two most basic approaches: finite differences and finite elements. Peter J. Olver is professor of mathematics at the University of Minnesota. His wide-ranging research interests are centered on the development of symmetry-based methods for differential equations and their manifold applications. He is the author of over 130 papers published in major scientific research journals as well as 4 other books, including the definitive Springer graduate text, Applications of Lie Groups to Differential Equations, and another undergraduate text, Applied Linear Algebra. A Solutions Manual for instrucors is available by clicking on “Selected Solutions Manual” under the Additional Information section on the right-hand side of this page. The post Introduction to Partial Differential Equations appeared first on 1Bookcase. |
| High Energy Cosmic Rays, 2nd Edition Posted: 20 Apr 2016 03:06 AM PDT  High Energy Cosmic Rays, 2nd Edition.This is a textbook for graduate students entering the field but at the same time a cosmic ray manual for high energy astrophysicists and its first part easy to read for the general astronomer. The first part describes the standard model of cosmic rays based on our understanding of modern particle physics. The acceleration scenario is presented in some detail in supernovae explosions as well as in the passage of cosmic rays through the Galaxy. Experimental data in the atmosphere as well as underground are compared with theoretical models. The second part is devoted to contemporary cosmic ray research like the analysis of shower phenomena, the discussion of the end of the cosmic spectrum and, finally, high energy neutrino astronomy. The post High Energy Cosmic Rays, 2nd Edition appeared first on 1Bookcase. |
| Excel 2010 for Social Science Statistics Posted: 20 Apr 2016 03:03 AM PDT  Excel 2010 for Social Science Statistics: A Guide to Solving Practical Problems.This is the first book to show the capabilities of Microsoft Excel to teach social science statistics effectively. It is a step-by-step exercise-driven guide for students and practitioners who need to master Excel to solve practical social science problems. If understanding statistics isn't your strongest suit, you are not especially mathematically-inclined, or if you are wary of computers, this is the right book for you. Excel, a widely available computer program for students and managers, is also an effective teaching and learning tool for quantitative analyses in social science courses. Its powerful computational ability and graphical functions make learning statistics much easier than in years past. However, Excel 2010 for Social Science Statistics: A Guide to Solving Practical Statistics Problems is the first book to capitalize on these improvements by teaching students and managers how to apply Excel to statistical techniques necessary in their courses and work. Each chapter explains statistical formulas and directs the reader to use Excel commands to solve specific, easy-to-understand social science problems. Practice problems are provided at the end of each chapter with their solutions in an Appendix. Separately, there is a full Practice Test (with answers in an Appendix) that allows readers to test what they have learned. Includes 164 Illustrations in color. The post Excel 2010 for Social Science Statistics appeared first on 1Bookcase. |
| Posted: 20 Apr 2016 03:00 AM PDT  Data Mining for Service (Studies in Big Data).Virtually all nontrivial and modern service related problems and systems involve data volumes and types that clearly fall into what is presently meant as “big data”, that is, are huge, heterogeneous, complex, distributed, etc. Data mining is a series of processes which include collecting and accumulating data, modeling phenomena, and discovering new information, and it is one of the most important steps to scientific analysis of the processes of services. Data mining application in services requires a thorough understanding of the characteristics of each service and knowledge of the compatibility of data mining technology within each particular service, rather than knowledge only in calculation speed and prediction accuracy. Varied examples of services provided in this book will help readers understand the relation between services and data mining technology. This book is intended to stimulate interest among researchers and practitioners in the relation between data mining technology and its application to other fields. The post Data Mining for Service appeared first on 1Bookcase. |
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