Practical Analysis Of Algorithms
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Practical Analysis Of Algorithms
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Author : Dana Vrajitoru
language : en
Publisher: Springer
Release Date : 2014-09-03
Practical Analysis Of Algorithms written by Dana Vrajitoru and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-09-03 with Computers categories.
This book introduces the essential concepts of algorithm analysis required by core undergraduate and graduate computer science courses, in addition to providing a review of the fundamental mathematical notions necessary to understand these concepts. Features: includes numerous fully-worked examples and step-by-step proofs, assuming no strong mathematical background; describes the foundation of the analysis of algorithms theory in terms of the big-Oh, Omega, and Theta notations; examines recurrence relations; discusses the concepts of basic operation, traditional loop counting, and best case and worst case complexities; reviews various algorithms of a probabilistic nature, and uses elements of probability theory to compute the average complexity of algorithms such as Quicksort; introduces a variety of classical finite graph algorithms, together with an analysis of their complexity; provides an appendix on probability theory, reviewing the major definitions and theorems used in the book.
A Practical Introduction To Data Structures And Algorithm Analysis
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Author : Clifford A. Shaffer
language : en
Publisher:
Release Date : 2001
A Practical Introduction To Data Structures And Algorithm Analysis written by Clifford A. Shaffer and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001 with Computers categories.
This practical text contains fairly "traditional" coverage of data structures with a clear and complete use of algorithm analysis, and some emphasis on file processing techniques as relevant to modern programmers. It fully integrates OO programming with these topics, as part of the detailed presentation of OO programming itself.Chapter topics include lists, stacks, and queues; binary and general trees; graphs; file processing and external sorting; searching; indexing; and limits to computation.For programmers who need a good reference on data structures.
An Introduction To The Analysis Of Algorithms
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Author : Robert Sedgewick
language : en
Publisher: Addison-Wesley
Release Date : 2013-01-18
An Introduction To The Analysis Of Algorithms written by Robert Sedgewick and has been published by Addison-Wesley this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-01-18 with Computers categories.
Despite growing interest, basic information on methods and models for mathematically analyzing algorithms has rarely been directly accessible to practitioners, researchers, or students. An Introduction to the Analysis of Algorithms, Second Edition, organizes and presents that knowledge, fully introducing primary techniques and results in the field. Robert Sedgewick and the late Philippe Flajolet have drawn from both classical mathematics and computer science, integrating discrete mathematics, elementary real analysis, combinatorics, algorithms, and data structures. They emphasize the mathematics needed to support scientific studies that can serve as the basis for predicting algorithm performance and for comparing different algorithms on the basis of performance. Techniques covered in the first half of the book include recurrences, generating functions, asymptotics, and analytic combinatorics. Structures studied in the second half of the book include permutations, trees, strings, tries, and mappings. Numerous examples are included throughout to illustrate applications to the analysis of algorithms that are playing a critical role in the evolution of our modern computational infrastructure. Improvements and additions in this new edition include Upgraded figures and code An all-new chapter introducing analytic combinatorics Simplified derivations via analytic combinatorics throughout The book’s thorough, self-contained coverage will help readers appreciate the field’s challenges, prepare them for advanced results—covered in their monograph Analytic Combinatorics and in Donald Knuth’s The Art of Computer Programming books—and provide the background they need to keep abreast of new research. "[Sedgewick and Flajolet] are not only worldwide leaders of the field, they also are masters of exposition. I am sure that every serious computer scientist will find this book rewarding in many ways." —From the Foreword by Donald E. Knuth
Practical Algorithms For Image Analysis With Cd Rom
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Author : Lawrence O'Gorman
language : en
Publisher: Cambridge University Press
Release Date : 2008-01-21
Practical Algorithms For Image Analysis With Cd Rom written by Lawrence O'Gorman and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-01-21 with Computers categories.
This new edition's CD-ROM now has both the source code, and a graphic interface to make it easier to use.
A Practical Introduction To Data Structures And Algorithm Analysis C Edition
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Author : Clifford A. Shaffer
language : en
Publisher:
Release Date : 2002
A Practical Introduction To Data Structures And Algorithm Analysis C Edition written by Clifford A. Shaffer and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002 with C++ (Computer program language). categories.
Algorithm Engineering
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Author : Matthias Müller-Hannemann
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-08-05
Algorithm Engineering written by Matthias Müller-Hannemann and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-08-05 with Computers categories.
Algorithms are essential building blocks of computer applications. However, advancements in computer hardware, which render traditional computer models more and more unrealistic, and an ever increasing demand for efficient solution to actual real world problems have led to a rising gap between classical algorithm theory and algorithmics in practice. The emerging discipline of Algorithm Engineering aims at bridging this gap. Driven by concrete applications, Algorithm Engineering complements theory by the benefits of experimentation and puts equal emphasis on all aspects arising during a cyclic solution process ranging from realistic modeling, design, analysis, robust and efficient implementations to careful experiments. This tutorial - outcome of a GI-Dagstuhl Seminar held in Dagstuhl Castle in September 2006 - covers the essential aspects of this process in ten chapters on basic ideas, modeling and design issues, analysis of algorithms, realistic computer models, implementation aspects and algorithmic software libraries, selected case studies, as well as challenges in Algorithm Engineering. Both researchers and practitioners in the field will find it useful as a state-of-the-art survey.
Practical Machine Learning For Data Analysis Using Python
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Author : Abdulhamit Subasi
language : en
Publisher: Academic Press
Release Date : 2020-06-05
Practical Machine Learning For Data Analysis Using Python written by Abdulhamit Subasi and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-05 with Computers categories.
Practical Machine Learning for Data Analysis Using Python is a problem solver’s guide for creating real-world intelligent systems. It provides a comprehensive approach with concepts, practices, hands-on examples, and sample code. The book teaches readers the vital skills required to understand and solve different problems with machine learning. It teaches machine learning techniques necessary to become a successful practitioner, through the presentation of real-world case studies in Python machine learning ecosystems. The book also focuses on building a foundation of machine learning knowledge to solve different real-world case studies across various fields, including biomedical signal analysis, healthcare, security, economics, and finance. Moreover, it covers a wide range of machine learning models, including regression, classification, and forecasting. The goal of the book is to help a broad range of readers, including IT professionals, analysts, developers, data scientists, engineers, and graduate students, to solve their own real-world problems. Offers a comprehensive overview of the application of machine learning tools in data analysis across a wide range of subject areas Teaches readers how to apply machine learning techniques to biomedical signals, financial data, and healthcare data Explores important classification and regression algorithms as well as other machine learning techniques Explains how to use Python to handle data extraction, manipulation, and exploration techniques, as well as how to visualize data spread across multiple dimensions and extract useful features
Practical Algorithms For Image Analysis With Cd Rom
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Author : Michael Seul
language : en
Publisher: Cambridge University Press
Release Date : 2000-02-13
Practical Algorithms For Image Analysis With Cd Rom written by Michael Seul and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000-02-13 with Computers categories.
This book offers guided access to a collection of algorithms for the digital manipulation and analysis of images. Written in classic 'cookbook' style, it reflects the authors' long experience in this field. For each task, they present a description and implementation of the most suitable procedure in easy-to-use form. The algorithms range from the simplest steps to advanced functions not commonly available for Windows users. Each self-contained section treats a single operation, describing typical situations requiring that operation and discussing the algorithm and implementation. Sections start with a header illustrating the nature of the procedure through a 'before' and 'after' pictorial example and a ready-reference listing typical applications, keywords, and related procedures. At the end of each section are annotated references and a display of program usage for the C programs on the accompanying CD-ROM. Every researcher or practitioner working with images will need this reference and software library.
Practical Algorithms For Image Analysis
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Author : Michael Seul
language : en
Publisher:
Release Date : 2000
Practical Algorithms For Image Analysis written by Michael Seul and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000 with categories.
The Discrete Math Workbook
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Author : Sergei Kurgalin
language : en
Publisher: Springer
Release Date : 2018-07-31
The Discrete Math Workbook written by Sergei Kurgalin and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-07-31 with Computers categories.
This practically-oriented textbook presents an accessible introduction to discrete mathematics through a substantial collection of classroom-tested exercises. Each chapter opens with concise coverage of the theory underlying the topic, reviewing the basic concepts and establishing the terminology, as well as providing the key formulae and instructions on their use. This is then followed by a detailed account of the most common problems in the area, before the reader is invited to practice solving such problems for themselves through a varied series of questions and assignments. Topics and features: provides an extensive set of exercises and examples of varying levels of complexity, suitable for both laboratory practical training and self-study; offers detailed solutions to many problems, applying commonly-used methods and computational schemes; introduces the fundamentals of mathematical logic, the theory of algorithms, Boolean algebra, graph theory, sets, relations, functions, and combinatorics; presents more advanced material on the design and analysis of algorithms, including asymptotic analysis, and parallel algorithms; includes reference lists of trigonometric and finite summation formulae in an appendix, together with basic rules for differential and integral calculus. This hands-on study guide is designed to address the core needs of undergraduate students training in computer science, informatics, and electronic engineering, emphasizing the skills required to develop and implement an algorithm in a specific programming language.