Essential Algorithms

Essential Algorithms Author Rod Stephens
ISBN-10 9781118797297
Release 2013-07-25
Pages 624
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A friendly and accessible introduction to the most useful algorithms Computer algorithms are the basic recipes for programming. Professional programmers need to know how to use algorithms to solve difficult programming problems. Written in simple, intuitive English, this book describes how and when to use the most practical classic algorithms, and even how to create new algorithms to meet future needs. The book also includes a collection of questions that can help readers prepare for a programming job interview. Reveals methods for manipulating common data structures such as arrays, linked lists, trees, and networks Addresses advanced data structures such as heaps, 2-3 trees, B-trees Addresses general problem-solving techniques such as branch and bound, divide and conquer, recursion, backtracking, heuristics, and more Reviews sorting and searching, network algorithms, and numerical algorithms Includes general problem-solving techniques such as brute force and exhaustive search, divide and conquer, backtracking, recursion, branch and bound, and more In addition, Essential Algorithms features a companion website that includes full instructor materials to support training or higher ed adoptions.

A Web Based Introduction to Programming

A Web Based Introduction to Programming Author Mike O'Kane
ISBN-10 1611634709
Release 2014
Pages 573
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A Web-Based Introduction to Programming is designed for use in introductory programming, programming logic and design, or Web programming courses, and for anyone seeking a painless way to learn the basics of programming by developing small Web applications. The book is clearly written, using consistent examples in every chapter and step-by-step descriptions of standard programming procedures. Each chapter follows precise learning outcomes that are accurately tested by the end-of-chapter quizzes and exercises.A Web-Based Introduction to Programming keeps the focus on the need for beginning programmers to learn essential syntax and control structures with minimal complexity. Each chapter focuses on a single topic and related material is provided in appendices. Students learn to convert requirements into algorithms, and then develop small Web-based applications using a combination of PHP and HTML.The chapter code exercises are designed to improve skill and confidence step-by-step: fixit exercises provide small programs that include a single error of some kind and help students develop their problem-solving abilities and debugging skills; modify exercises provide working programs that must be modified to perform a somewhat different or additional function (these exercises test students' ability to read, understand, and adapt existing code); code completion exercises allow students to apply all concepts and tools covered in the chapter by developing new applications; and all required software is provided and can be installed quickly and easily in minutes under Windows, Macintosh OS X or Linux. The software can be installed entirely on a USB drive so that students can carry their complete work environment with them (no need for special classroom installation).

Mastering Algorithms with Perl

Mastering Algorithms with Perl Author Jarkko Hietaniemi
ISBN-10 9781449307196
Release 1999-08-18
Pages 706
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Many programmers would love to use Perl for projects that involve heavy lifting, but miss the many traditional algorithms that textbooks teach for other languages. Computer scientists have identified many techniques that a wide range of programs need, such as: Fuzzy pattern matching for text (identify misspellings!) Finding correlations in data Game-playing algorithms Predicting phenomena such as Web traffic Polynomial and spline fitting Using algorithms explained in this book, you too can carry out traditional programming tasks in a high-powered, efficient, easy-to-maintain manner with Perl.This book assumes a basic understanding of Perl syntax and functions, but not necessarily any background in computer science. The authors explain in a readable fashion the reasons for using various classic programming techniques, the kind of applications that use them, and -- most important -- how to code these algorithms in Perl.If you are an amateur programmer, this book will fill you in on the essential algorithms you need to solve problems like an expert. If you have already learned algorithms in other languages, you will be surprised at how much different (and often easier) it is to implement them in Perl. And yes, the book even has the obligatory fractal display program.There have been dozens of books on programming algorithms, some of them excellent, but never before has there been one that uses Perl.The authors include the editor of The Perl Journal and master librarian of CPAN; all are contributors to CPAN and have archived much of the code in this book there."This book was so exciting I lost sleep reading it." Tom Christiansen

The 2d Games Journey

The 2d Games Journey Author Dana Vrajitoru
ISBN-10 1492269573
Release 2013-08
Pages 218
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This book represents an introduction to 2D games using Flash ActionScript 3.0 as a platform. It approaches the field in a progressive way, classifying games in categories based on essential features and difficulty. It combines discussions on practical games and implementation details with topics pertaining to games theory. Our intention is to familiarize the reader with a set of games with enough variety to provide a solid background for approaching any other 2D game with ease.

Algorithmen Eine Einf hrung

Algorithmen   Eine Einf  hrung Author Thomas H. Cormen
ISBN-10 9783110522013
Release 2013-01-01
Pages 1339
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Der "Cormen" bietet eine umfassende und vielseitige Einführung in das moderne Studium von Algorithmen. Es stellt viele Algorithmen Schritt für Schritt vor, behandelt sie detailliert und macht deren Entwurf und deren Analyse allen Leserschichten zugänglich. Sorgfältige Erklärungen zur notwendigen Mathematik helfen, die Analyse der Algorithmen zu verstehen. Den Autoren ist es dabei geglückt, Erklärungen elementar zu halten, ohne auf Tiefe oder mathematische Exaktheit zu verzichten. Jedes der weitgehend eigenständig gestalteten Kapitel stellt einen Algorithmus, eine Entwurfstechnik, ein Anwendungsgebiet oder ein verwandtes Thema vor. Algorithmen werden beschrieben und in Pseudocode entworfen, der für jeden lesbar sein sollte, der schon selbst ein wenig programmiert hat. Zahlreiche Abbildungen verdeutlichen, wie die Algorithmen arbeiten. Ebenfalls angesprochen werden Belange der Implementierung und andere technische Fragen, wobei, da Effizienz als Entwurfskriterium betont wird, die Ausführungen eine sorgfältige Analyse der Laufzeiten der Programme mit ein schließen. Über 1000 Übungen und Problemstellungen und ein umfangreiches Quellen- und Literaturverzeichnis komplettieren das Lehrbuch, dass durch das ganze Studium, aber auch noch danach als mathematisches Nachschlagewerk oder als technisches Handbuch nützlich ist. Für die dritte Auflage wurde das gesamte Buch aktualisiert. Die Änderungen sind vielfältig und umfassen insbesondere neue Kapitel, überarbeiteten Pseudocode, didaktische Verbesserungen und einen lebhafteren Schreibstil. So wurden etwa - neue Kapitel zu van-Emde-Boas-Bäume und mehrfädigen (engl.: multithreaded) Algorithmen aufgenommen, - das Kapitel zu Rekursionsgleichungen überarbeitet, sodass es nunmehr die Teile-und-Beherrsche-Methode besser abdeckt, - die Betrachtungen zu dynamischer Programmierung und Greedy-Algorithmen überarbeitet; Memoisation und der Begriff des Teilproblem-Graphen als eine Möglichkeit, die Laufzeit eines auf dynamischer Programmierung beruhender Algorithmus zu verstehen, werden eingeführt. - 100 neue Übungsaufgaben und 28 neue Problemstellungen ergänzt. Umfangreiches Dozentenmaterial (auf englisch) ist über die Website des US-Verlags verfügbar.

Machine Learning in Python

Machine Learning in Python Author Michael Bowles
ISBN-10 9781118961766
Release 2015-03-24
Pages 360
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Learn a simpler and more effective way to analyze data and predict outcomes with Python Machine Learning in Python shows you how to successfully analyze data using only two core machine learning algorithms, and how to apply them using Python. By focusing on two algorithm families that effectively predict outcomes, this book is able to provide full descriptions of the mechanisms at work, and the examples that illustrate the machinery with specific, hackable code. The algorithms are explained in simple terms with no complex math and applied using Python, with guidance on algorithm selection, data preparation, and using the trained models in practice. You will learn a core set of Python programming techniques, various methods of building predictive models, and how to measure the performance of each model to ensure that the right one is used. The chapters on penalized linear regression and ensemble methods dive deep into each of the algorithms, and you can use the sample code in the book to develop your own data analysis solutions. Machine learning algorithms are at the core of data analytics and visualization. In the past, these methods required a deep background in math and statistics, often in combination with the specialized R programming language. This book demonstrates how machine learning can be implemented using the more widely used and accessible Python programming language. Predict outcomes using linear and ensemble algorithm families Build predictive models that solve a range of simple and complex problems Apply core machine learning algorithms using Python Use sample code directly to build custom solutions Machine learning doesn't have to be complex and highly specialized. Python makes this technology more accessible to a much wider audience, using methods that are simpler, effective, and well tested. Machine Learning in Python shows you how to do this, without requiring an extensive background in math or statistics.

Beginning Software Engineering

Beginning Software Engineering Author Rod Stephens
ISBN-10 9781118969175
Release 2015-03-02
Pages 480
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A complete introduction to building robust and reliable software Beginning Software Engineering demystifies the software engineering methodologies and techniques that professional developers use to design and build robust, efficient, and consistently reliable software. Free of jargon and assuming no previous programming, development, or management experience, this accessible guide explains important concepts and techniques that can be applied to any programming language. Each chapter ends with exercises that let you test your understanding and help you elaborate on the chapter's main concepts. Everything you need to understand waterfall, Sashimi, agile, RAD, Scrum, Kanban, Extreme Programming, and many other development models is inside! Describes in plain English what software engineering is Explains the roles and responsibilities of team members working on a software engineering project Outlines key phases that any software engineering effort must handle to produce applications that are powerful and dependable Details the most popular software development methodologies and explains the different ways they handle critical development tasks Incorporates exercises that expand upon each chapter's main ideas Includes an extensive glossary of software engineering terms

Logic Minimization Algorithms for VLSI Synthesis

Logic Minimization Algorithms for VLSI Synthesis Author Robert K. Brayton
ISBN-10 0898381649
Release 1984-08-31
Pages 194
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The roots of the project which culminates with the writing of this book can be traced to the work on logic synthesis started in 1979 at the IBM Watson Research Center and at University of California, Berkeley. During the preliminary phases of these projects, the impor tance of logic minimization for the synthesis of area and performance effective circuits clearly emerged. In 1980, Richard Newton stirred our interest by pointing out new heuristic algorithms for two-level logic minimization and the potential for improving upon existing approaches. In the summer of 1981, the authors organized and participated in a seminar on logic manipulation at IBM Research. One of the goals of the seminar was to study the literature on logic minimization and to look at heuristic algorithms from a fundamental and comparative point of view. The fruits of this investigation were surprisingly abundant: it was apparent from an initial implementation of recursive logic minimiza tion (ESPRESSO-I) that, if we merged our new results into a two-level minimization program, an important step forward in automatic logic synthesis could result. ESPRESSO-II was born and an APL implemen tation was created in the summer of 1982. The results of preliminary tests on a fairly large set of industrial examples were good enough to justify the publication of our algorithms. It is hoped that the strength and speed of our minimizer warrant its Italian name, which denotes both express delivery and a specially-brewed black coffee.

The Dissimilarity Representation for Pattern Recognition

The Dissimilarity Representation for Pattern Recognition Author El?bieta P?kalska
ISBN-10 9789812565303
Release 2005
Pages 607
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This book provides a fundamentally new approach to pattern recognition in which objects are characterized by relations to other objects instead of by using features or models. This 'dissimilarity representation' bridges the gap between the traditionally opposing approaches of statistical and structural pattern recognition.Physical phenomena, objects and events in the world are related in various and often complex ways. Such relations are usually modeled in the form of graphs or diagrams. While this is useful for communication between experts, such representation is difficult to combine and integrate by machine learning procedures. However, if the relations are captured by sets of dissimilarities, general data analysis procedures may be applied for analysis.With their detailed description of an unprecedented approach absent from traditional textbooks, the authors have crafted an essential book for every researcher and systems designer studying or developing pattern recognition systems.

Foundations of Algorithms

Foundations of Algorithms Author Professor Emeritus Rutgers University School of Health Related Professions Craig L Scanlan
ISBN-10 9781284049206
Release 2014-03-31
Pages 685
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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"


Sensemaking Author Christian Madsbjerg
ISBN-10 9781408708385
Release 2017-03-21
Pages 240
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Humans have become subservient to algorithms. Every day brings a new Moneyball fix - a maths whiz who will crack open an industry with clean fact-based analysis rather than human intuition and experience. As a result, we have stopped thinking. Machines do it for us. Christian Madsbjerg argues that our fixation with data often masks stunning deficiencies, and the risks for humankind are enormous. Blind devotion to number crunching imperils our businesses, our educations, our governments, and our life savings. Too many companies have lost touch with the humanity of their customers, while marginalising workers with arts-based skills. Contrary to popular thinking, Madsbjerg shows how many of today's biggest success stories stem not from 'quant' thinking but from deep, nuanced engagement with culture, language, and history. He calls his method sensemaking. In this landmark book, Madsbjerg lays out five principles for how business leaders, entrepreneurs, and individuals can use it to solve their thorniest problems. He profiles companies using sensemaking to connect with new customers, and takes readers inside the work process of sensemaking 'connoisseurs' like investor George Soros, architect Bjarke Ingels, and others. Both practical and philosophical, Sensemaking is a powerful rejoinder to corporate groupthink and an indispensable resource for leaders and innovators who want to stand out from the pack.

Max linear Systems Theory and Algorithms

Max linear Systems  Theory and Algorithms Author Peter Butkovič
ISBN-10 1849962995
Release 2010-08-05
Pages 274
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Recent years have seen a significant rise of interest in max-linear theory and techniques. Specialised international conferences and seminars or special sessions devoted to max-algebra have been organised. This book aims to provide a first detailed and self-contained account of linear-algebraic aspects of max-algebra for general (that is both irreducible and reducible) matrices. Among the main features of the book is the presentation of the fundamental max-algebraic theory (Chapters 1-4), often scattered in research articles, reports and theses, in one place in a comprehensive and unified form. This presentation is made with all proofs and in full generality (that is for both irreducible and reducible matrices). Another feature is the presence of advanced material (Chapters 5-10), most of which has not appeared in a book before and in many cases has not been published at all. Intended for a wide-ranging readership, this book will be useful for anyone with basic mathematical knowledge (including undergraduate students) who wish to learn fundamental max-algebraic ideas and techniques. It will also be useful for researchers working in tropical geometry or idempotent analysis.

A Guided Tour of Relational Databases and Beyond

A Guided Tour of Relational Databases and Beyond Author Mark Levene
ISBN-10 1852330082
Release 1999-05-28
Pages 625
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this book provides an overview of database modeling with the Entity-Relationship (ER) model and the relational model. The book focuses On the primary achievements in relational database theory, including query languages, integrity constraints, database design, computable queries; and concurrency control.

Recommender Systems and the Social Web

Recommender Systems and the Social Web Author Fatih Gedikli
ISBN-10 9783658019488
Release 2013-03-29
Pages 112
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​There is an increasing demand for recommender systems due to the information overload users are facing on the Web. The goal of a recommender system is to provide personalized recommendations of products or services to users. With the advent of the Social Web, user-generated content has enriched the social dimension of the Web. As user-provided content data also tells us something about the user, one can learn the user’s individual preferences from the Social Web. This opens up completely new opportunities and challenges for recommender systems research. Fatih Gedikli deals with the question of how user-provided tagging data can be used to build better recommender systems. A tag recommender algorithm is proposed which recommends tags for users to annotate their favorite online resources. The author also proposes algorithms which exploit the user-provided tagging data and produce more accurate recommendations. On the basis of this idea, he shows how tags can be used to explain to the user the automatically generated recommendations in a clear and intuitively understandable form. With his book, Fatih Gedikli gives us an outlook on the next generation of recommendation systems in the Social Web sphere.

Text Algorithms

Text Algorithms Author Maxime Crochemore
ISBN-10 9780195086096
Release 1994
Pages 412
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This much-needed book on the design of algorithms and data structures for text processing emphasizes both theoretical foundations and practical applications. It is intended to serve both as a textbook for courses on algorithm design, especially those related to text processing, and as a reference for computer science professionals. The work takes a unique approach, one that goes more deeply into its topic than other more general books. It contains both classical algorithms and recent results of research on the subject. The book is the first text to contain a collection of a wide range of text algorithms, many of them quite new and appearing here for the first time. Other algorithms, while known by reputation, have never been published in the journal literature. Two such important algorithms are those of Karp, Miller and Rosenberg, and that of Weiner. Here they are presented together for the fist time. The core of the book is the material on suffix trees and subword graphs, applications of these data structures, new approaches to time-space optimal string-matching, and text compression. Also covered are basic parallel algorithms for text problems. Applications of all these algorithms are given for problems involving data retrieval systems, treatment of natural languages, investigation of genomes, data compression software, and text processing tools. From the theoretical point of view. the book is a goldmine of paradigms for the development of efficient algorithms, providing the necessary foundation to creating practical software dealing with sequences. A crucial point in the authors' approach is the development of a methodology for presenting text algorithms so they can be fully understood. Throughout, the book emphasizes the efficiency of algorithms, holding that the essence of their usefulness depends on it. This is especially important since the algorithms described here will find application in "Big Science" areas like molecular sequence analysis where the explosive growth of data has caused problems for the current generation of software. Finally, with its development of theoretical background, the book can be considered as a mathematical foundation for the analysis and production of text processing algorithms.

Chinese Handwriting Recognition An Algorithmic Perspective

Chinese Handwriting Recognition  An Algorithmic Perspective Author Tonghua Su
ISBN-10 9783642318122
Release 2013-01-11
Pages 124
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Designing machines that can read handwriting like human beings has been an ambitious goal for more than half a century, driving talented researchers to explore diverse approaches. Obstacles have often been encountered that at first appeared insurmountable but were indeed overcome before long. Yet some open issues remain to be solved. As an indispensable branch, Chinese handwriting recognition has been termed as one of the most difficult Pattern Recognition tasks. Chinese handwriting recognition poses its own unique challenges, such as huge variations in strokes, diversity of writing styles, and a large set of confusable categories. With ever-increasing training data, researchers have pursued elaborate algorithms to discern characters from different categories and compensate for the sample variations within the same category. As a result, Chinese handwriting recognition has evolved substantially and amazing achievements can be seen. This book introduces integral algorithms used in Chinese handwriting recognition and the applications of Chinese handwriting recogniers. The first part of the book covers both widespread canonical algorithms to a reliable recognizer and newly developed scalable methods in Chinese handwriting recognition. The recognition of Chinese handwritten text is presented systematically, including instructive guidelines for collecting samples, novel recognition paradigms, distributed discriminative learning of appearance models and distributed estimation of contextual models for large categories, in addition to celebrated methods, e.g. Gradient features, MQDF and HMMs. In the second part of this book, endeavors are made to create a friendlier human-machine interface through application of Chinese handwriting recognition. Four scenarios are exemplified: grid-assisted input, shortest moving input, handwritten micro-blog, and instant handwriting messenger. All the while, the book moves from basic to more complex approaches, also providing a list for further reading with literature comments.

Data Mining Algorithms

Data Mining Algorithms Author Pawel Cichosz
ISBN-10 9781118332580
Release 2015-01-27
Pages 720
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"This book narrows down the scope of data mining by adopting a heavily modeling-oriented perspective"--