Foundations of Algorithms PDF Download
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Author: Richard E. Neapolitan
Publisher: Jones & Bartlett Learning
ISBN: 0763782505
Category : Computers
Languages : en
Pages : 647
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Book Description
Data Structures & Theory of Computation
Author: Richard E. Neapolitan
Publisher: Jones & Bartlett Publishers
ISBN: 1284049205
Category : Algorithms
Languages : en
Pages : 694
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Book Description
Author: Richard E. Neapolitan
Publisher: Jones & Bartlett Learning
ISBN: 0763782505
Category : Computers
Languages : en
Pages : 647
Get Book Here
Book Description
Data Structures & Theory of Computation
Author: Richard Neapolitan
Publisher: Jones & Bartlett Learning
ISBN: 1284049191
Category : Computers
Languages : en
Pages : 694
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Book Description
Foundations of Algorithms, Fifth Edition offers a well-balanced presentation of algorithm design, complexity analysis of algorithms, and computational complexity. Ideal for any computer science students with a background in college algebra and discrete structures, the text presents mathematical concepts using standard English and simple notation to maximize accessibility and user-friendliness. Concrete examples, appendices reviewing essential mathematical concepts, and a student-focused approach reinforce theoretical explanations and promote learning and retention. C++ and Java pseudocode help students better understand complex algorithms. A chapter on numerical algorithms includes a review of basic number theory, Euclid's Algorithm for finding the greatest common divisor, a review of modular arithmetic, an algorithm for solving modular linear equations, an algorithm for computing modular powers, and the new polynomial-time algorithm for determining whether a number is prime.The revised and updated Fifth Edition features an all-new chapter on genetic algorithms and genetic programming, including approximate solutions to the traveling salesperson problem, an algorithm for an artificial ant that navigates along a trail of food, and an application to financial trading. With fully updated exercises and examples throughout and improved instructor resources including complete solutions, an Instructor’s Manual and PowerPoint lecture outlines, Foundations of Algorithms is an essential text for undergraduate and graduate courses in the design and analysis of algorithms. Key features include:• The only text of its kind with a chapter on genetic algorithms• Use of C++ and Java pseudocode to help students better understand complex algorithms• No calculus background required• Numerous clear and student-friendly examples throughout the text• Fully updated exercises and examples throughout• Improved instructor resources, including complete solutions, an Instructor’s Manual, and PowerPoint lecture outlines
Author: Robert E. Schapire
Publisher: MIT Press
ISBN: 0262526034
Category : Computers
Languages : en
Pages : 544
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Book Description
An accessible introduction and essential reference for an approach to machine learning that creates highly accurate prediction rules by combining many weak and inaccurate ones. Boosting is an approach to machine learning based on the idea of creating a highly accurate predictor by combining many weak and inaccurate “rules of thumb.” A remarkably rich theory has evolved around boosting, with connections to a range of topics, including statistics, game theory, convex optimization, and information geometry. Boosting algorithms have also enjoyed practical success in such fields as biology, vision, and speech processing. At various times in its history, boosting has been perceived as mysterious, controversial, even paradoxical. This book, written by the inventors of the method, brings together, organizes, simplifies, and substantially extends two decades of research on boosting, presenting both theory and applications in a way that is accessible to readers from diverse backgrounds while also providing an authoritative reference for advanced researchers. With its introductory treatment of all material and its inclusion of exercises in every chapter, the book is appropriate for course use as well. The book begins with a general introduction to machine learning algorithms and their analysis; then explores the core theory of boosting, especially its ability to generalize; examines some of the myriad other theoretical viewpoints that help to explain and understand boosting; provides practical extensions of boosting for more complex learning problems; and finally presents a number of advanced theoretical topics. Numerous applications and practical illustrations are offered throughout.
Author: Michael T. Goodrich
Publisher: John Wiley & Sons
ISBN: 0471383651
Category : Computers
Languages : en
Pages : 722
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Book Description
Michael Goodrich and Roberto Tamassia, authors of the successful, Data Structures and Algorithms in Java, 2/e, have written Algorithm Engineering, a text designed to provide a comprehensive introduction to the design, implementation and analysis of computer algorithms and data structures from a modern perspective. This book offers theoretical analysis techniques as well as algorithmic design patterns and experimental methods for the engineering of algorithms. Market: Computer Scientists; Programmers.
Author: Adam Drozdek
Publisher: Cengage Learning
ISBN: 9781133608424
Category : Computers
Languages : en
Pages : 0
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Book Description
Strengthen your understanding of data structures and their algorithms for the foundation you need to successfully design, implement and maintain virtually any software system. Theoretical, yet practical, DATA STRUCUTRES AND ALGORITHMS IN C++, 4E by experienced author Adam Drosdek highlights the fundamental connection between data structures and their algorithms, giving equal weight to the practical implementation of data structures and the theoretical analysis of algorithms and their efficiency. This edition provides critical new coverage of treaps, k-d trees and k-d B-trees, generational garbage collection, and other advanced topics such as sorting methods and a new hashing technique. Abundant C++ code examples and a variety of case studies provide valuable insights into data structures implementation. DATA STRUCTURES AND ALGORITHMS IN C++ provides the balance of theory and practice to prepare readers for a variety of applications in a modern, object-oriented paradigm. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.
Author: Art Gittleman
Publisher: Jones & Bartlett Learning
ISBN: 9780763725938
Category : Business & Economics
Languages : en
Pages : 372
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Book Description
C# .NET Illuminated is an introductory programming textbook that takes a step-by-step approach to event-driven programming and rapid application development using Microsoft Visual Studio .NET. Readers learn how to maximize the power of the C# language and the Visual Studio .NET environment through a hands-on, highly visual approach complete with numerous examples, sample applications, and programming exercises. Features designed to reinforce key skills and concepts are found throughout, making this book ideal for use in a classroom/lab setting or as a self-study guide.
Author: Frank F. Tsui
Publisher: Jones & Bartlett Learning
ISBN: 9780763725464
Category : Computers
Languages : en
Pages : 366
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Book Description
Computer Architecture/Software Engineering
Author: Richard E. Neapolitan
Publisher: Jones & Bartlett Publishers
ISBN:
Category : Business & Economics
Languages : en
Pages : 550
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Book Description
Foundations of Algorithms Using C++ Pseudocode offers a well-balanced presentation on designing algorithms, complexity analysis of algorithms, & computational complexity that is accessible to mainstream computer science students who have a background in college algebra & discrete structures. To support their approach, the authors present mathematical concepts using Standard English & a simpler notation than is found in most texts. A review of essential mathematical concepts is presented in three appendices. In addition, they reinforce the explanations with numerous concrete examples to help students grasp theoretical concepts.
Author: Shai Shalev-Shwartz
Publisher: Cambridge University Press
ISBN: 1107057132
Category : Computers
Languages : en
Pages : 415
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Book Description
Introduces machine learning and its algorithmic paradigms, explaining the principles behind automated learning approaches and the considerations underlying their usage.
