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Top text books mentioned on stackoverflow.com

Pattern Recognition and Machine Learning

Christopher M. Bishop

The field of pattern recognition has undergone substantial development over the years. This book reflects these developments while providing a grounding in the basic concepts of pattern recognition and machine learning. It is aimed at advanced undergraduates or first year PhD students, as well as researchers and practitioners.

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Compressed Image File Formats

John Miano

Since not all graphic formats are of equal complexity, author John Miano does not simply choose a number of file formats and devote a chapter to each one. Instead, he offers additional coverage for the more complex image file formats like PNG (a new standard) and JPEG, while providing all information necessary to use the simpler file formats. While including the well-documented BMP, XBM, and GIF formats for completeness, along with some of their less-covered features, this book gives the most space to the more intricate PNG and JPEG, from basic concepts to creating and reading actual files. Among its highlights, this book covers: -- JPEG Huffman coding, including decoding sequential mode JPEG images and creating sequential JPEG files-- Optimizing the DCT-- Portable Network Graphics format (PNG), including decompressing PNG image data and creating PNG files-- Windows BMP, XBM, and GIF

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Algorithms on Strings, Trees and Sequences

Dan Gusfield

String algorithms are a traditional area of study in computer science. In recent years their importance has grown dramatically with the huge increase of electronically stored text and of molecular sequence data (DNA or protein sequences) produced by various genome projects. This 1997 book is a general text on computer algorithms for string processing. In addition to pure computer science, the book contains extensive discussions on biological problems that are cast as string problems, and on methods developed to solve them. It emphasises the fundamental ideas and techniques central to today's applications. New approaches to this complex material simplify methods that up to now have been for the specialist alone. With over 400 exercises to reinforce the material and develop additional topics, the book is suitable as a text for graduate or advanced undergraduate students in computer science, computational biology, or bio-informatics. Its discussion of current algorithms and techniques also makes it a reference for professionals.

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Introduction to Machine Learning

Ethem Alpaydin

A new edition of an introductory text in machine learning that gives a unified treatment of machine learning problems and solutions.

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Natural Language Processing with Python

Steven Bird, Ewan Klein, Edward Loper

Presents information on how to write Python programs that will work with unstructured text.

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Unix Power Tools

Shelley Powers

By its very nature, Unix is a " power tools " environment. Even beginning Unix users quickly grasp that immense power exists in shell programming, aliases and history mechanisms, and various editing tools. Nonetheless, few users ever really master the power available to them with Unix. There is just too much to learn! Unix Power Tools, Third Edition, literally contains thousands of tips, scripts, and techniques that make using Unix easier, more effective, and even more fun. This book is organized into hundreds of short articles with plenty of references to other sections that keep you flipping from new article to new article. You'll find the book hard to put down as you uncover one interesting tip after another. With the growing popularity of Linux and the advent of Mac OS X, Unix has metamorphosed into something new and exciting. With Unix no longer perceived as a difficult operating system, more and more users are discovering its advantages for the first time. The latest edition of this best-selling favorite is loaded with advice about almost every aspect of Unix, covering all the new technologies that users need to know. In addition to vital information on Linux, Mac OS X, and BSD, Unix Power Tools, Third Edition, now offers more coverage of bcash, zsh, and new shells, along with discussions about modern utilities and applications. Several sections focus on security and Internet access, and there is a new chapter on access to Unix from Windows, addressing the heterogeneous nature of systems today. You'll also find expanded coverage of software installation and packaging, as well as basic information on Perl and Python. The book's accompanying web site provides some of the best software available to Unix users, which you can download and add to your own set of power tools. Whether you are a newcomer or a Unix power user, you'll find yourself thumbing through the gold mine of information in this new edition of Unix Power Tools to add to your store of knowledge. Want to try something new? Check this book first, and you're sure to find a tip or trick that will prevent you from learning things the hard way.

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Integrating and Extending BIRT

Jason Weathersby, Tom Bondur, Iana Chatalbasheva, Don French

Revised and expanded to include brand new features in just released new version of BIRT. • • Topics discussed include: Installing and deploying BIRT; Understanding BIRT architecture; Scripting and integrating • Revised and expanded to include: Tag library descriptions; BIRT Web Viewer, XML Report rendering; Open Data Access (ODA) • Authors are members of the BIRT development team. The world-wide developer community has downloaded over three million copies of BIRT (Business Intelligence and Reporting Tools) from the Eclipse web site. Built on the open-source Eclipse platform, BIRT is a powerful reporting system that provides an end-to-end solution, from creating and deploying reports to integrating report capabilities in enterprise applications. The second of a two-book series on business intelligence and reporting technology, Integrating and Extending BIRT, Second Edition introduces programmers to BIRT architecture and the reporting framework. BIRT technology makes it possible for a programmer to build a customized report using scripting and BIRT APIs. A programmer can also extend the BIRT framework by creating a new plug-in using the Eclipse Plug-in Development Environment. This book provides extensive examples on how to build plug-ins to extend the features of the BIRT framework.

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Pro .NET 2.0 Windows Forms and Custom Controls in C#

Matthew MacDonald

*The first advanced book offering important .NET 2.0 insights into C# and Windows Forms *Explains taking .NET controls to highest level for programmers, with advanced customizations *Follows the successful formula of the previous edition (1590590457), examining all the .NET controls from old staples to the new .NET 2.0 controls

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An Introduction to Support Vector Machines and Other Kernel-based Learning Methods

Nello Cristianini, John Shawe-Taylor

This is the first comprehensive introduction to Support Vector Machines (SVMs), a new generation learning system based on recent advances in statistical learning theory. SVMs deliver state-of-the-art performance in real-world applications such as text categorisation, hand-written character recognition, image classification, biosequences analysis, etc., and are now established as one of the standard tools for machine learning and data mining. Students will find the book both stimulating and accessible, while practitioners will be guided smoothly through the material required for a good grasp of the theory and its applications.

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Learning with Kernels

Bernhard Schölkopf, Alexander J. Smola

A comprehensive introduction to Support Vector Machines and related kernel methods.

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Based on two highly acclaimed PBS documentaries, this book uses the metaphor of a disease to tackle a very serious subject: the damage done - to our health, out families, our communities, and our environment - by the obsessive quest for material gain. The authors show that problems like loneliness, rising debt, longer working hours, environmental pollution, family conflict and rampant commercialism are actually symptoms caused by the same 'disease': affluenza.

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PDF Explained

John Whitington

Explains the features, components, and applications of PDF documents; demonstrates through text and examples how to create a document; and describes the format's history and software options.

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Fundamentals of Predictive Text Mining

Sholom M. Weiss, Nitin Indurkhya, Tong Zhang

One consequence of the pervasive use of computers is that most documents originate in digital form. Widespread use of the Internet makes them readily available. Text mining – the process of analyzing unstructured natural-language text – is concerned with how to extract information from these documents. Developed from the authors’ highly successful Springer reference on text mining, Fundamentals of Predictive Text Mining is an introductory textbook and guide to this rapidly evolving field. Integrating topics spanning the varied disciplines of data mining, machine learning, databases, and computational linguistics, this uniquely useful book also provides practical advice for text mining. In-depth discussions are presented on issues of document classification, information retrieval, clustering and organizing documents, information extraction, web-based data-sourcing, and prediction and evaluation. Background on data mining is beneficial, but not essential. Where advanced concepts are discussed that require mathematical maturity for a proper understanding, intuitive explanations are also provided for less advanced readers. Topics and features: presents a comprehensive, practical and easy-to-read introduction to text mining; includes chapter summaries, useful historical and bibliographic remarks, and classroom-tested exercises for each chapter; explores the application and utility of each method, as well as the optimum techniques for specific scenarios; provides several descriptive case studies that take readers from problem description to systems deployment in the real world; includes access to industrial-strength text-mining software that runs on any computer; describes methods that rely on basic statistical techniques, thus allowing for relevance to all languages (not just English); contains links to free downloadable software and other supplementary instruction material. Fundamentals of Predictive Text Mining is an essential resource for IT professionals and managers, as well as a key text for advanced undergraduate computer science students and beginning graduate students. Dr. Sholom M. Weiss is a Research Staff Member with the IBM Predictive Modeling group, in Yorktown Heights, New York, and Professor Emeritus of Computer Science at Rutgers University. Dr. Nitin Indurkhya is Professor at the School of Computer Science and Engineering, University of New South Wales, Australia, as well as founder and president of data-mining consulting company Data-Miner Pty Ltd. Dr. Tong Zhang is Associate Professor at the Department of Statistics and Biostatistics at Rutgers University, New Jersey.

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Practical Text Mining and Statistical Analysis for Non-structured Text Data Applications

Gary Miner

The world contains an unimaginably vast amount of digital information which is getting ever vaster ever more rapidly. This makes it possible to do many things that previously could not be done: spot business trends, prevent diseases, combat crime and so on. Managed well, the textual data can be used to unlock new sources of economic value, provide fresh insights into science and hold governments to account. As the Internet expands and our natural capacity to process the unstructured text that it contains diminishes, the value of text mining for information retrieval and search will increase dramatically. This comprehensive professional reference brings together all the information, tools and methods a professional will need to efficiently use text mining applications and statistical analysis. The Handbook of Practical Text Mining and Statistical Analysis for Non-structured Text Data Applications presents a comprehensive how- to reference that shows the user how to conduct text mining and statistically analyze results. In addition to providing an in-depth examination of core text mining and link detection tools, methods and operations, the book examines advanced preprocessing techniques, knowledge representation considerations, and visualization approaches. Finally, the book explores current real-world, mission-critical applications of text mining and link detection using real world example tutorials in such varied fields as corporate, finance, business intelligence, genomics research, and counterterrorism activities. -Extensive case studies, most in a tutorial format, allow the reader to 'click through' the example using a software program, thus learning to conduct text mining analyses in the most rapid manner of learning possible -Numerous examples, tutorials, power points and datasets available via companion website on Elsevierdirect.com -Glossary of text mining terms provided in the appendix

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