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.

Essential Algorithms

Essential Algorithms Author Rod Stephens
ISBN-10 9781118612101
Release 2013-08-12
Pages 624
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Exercises; Chapter 18: Distributed Algorithms; Types of Parallelism; Distributed Algorithms; Summary; Exercises; Chapter 19: Interview Puzzles; Asking Interview Puzzle Questions; Answering Interview Puzzle Questions; Summary; Exercises; Appendix A: Summary of Algorithmic Concepts; Chapter 1: Algorithm Basics; Chapter 2: Numeric Algorithms; Chapter 3: Linked Lists; Chapter 4: Arrays; Chapter 5: Stacks and Queues; Chapter 6: Sorting; Chapter 7: Searching; Chapter 8: Hash Tables; Chapter 9: Recursion; Chapter 10: Trees; Chapter 11: Balanced Trees; Chapter 12: Decision Trees.

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 9781449307271
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 Algorithm Design Manual

The Algorithm Design Manual Author Steven S Skiena
ISBN-10 9781848000704
Release 2009-04-05
Pages 730
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This newly expanded and updated second edition of the best-selling classic continues to take the "mystery" out of designing algorithms, and analyzing their efficacy and efficiency. Expanding on the first edition, the book now serves as the primary textbook of choice for algorithm design courses while maintaining its status as the premier practical reference guide to algorithms for programmers, researchers, and students. The reader-friendly Algorithm Design Manual provides straightforward access to combinatorial algorithms technology, stressing design over analysis. The first part, Techniques, provides accessible instruction on methods for designing and analyzing computer algorithms. The second part, Resources, is intended for browsing and reference, and comprises the catalog of algorithmic resources, implementations and an extensive bibliography. NEW to the second edition: • Doubles the tutorial material and exercises over the first edition • Provides full online support for lecturers, and a completely updated and improved website component with lecture slides, audio and video • Contains a unique catalog identifying the 75 algorithmic problems that arise most often in practice, leading the reader down the right path to solve them • Includes several NEW "war stories" relating experiences from real-world applications • Provides up-to-date links leading to the very best algorithm implementations available in C, C++, and Java

Beginning Algorithms

Beginning Algorithms Author Simon Harris
ISBN-10 9780471783831
Release 2005-11-11
Pages 564
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Beginning Algorithms A good understanding of algorithms, and the knowledge of when to apply them, is crucial to producing software that not only works correctly, but also performs efficiently. This is the only book to impart all this essential information-from the basics of algorithms, data structures, and performance characteristics to the specific algorithms used in development and programming tasks. Packed with detailed explanations and instructive examples, the book begins by offering you some fundamental data structures and then goes on to explain various sorting algorithms. You'll then learn efficient practices for storing and searching by way of hashing, trees, sets, and maps. The authors also share tips on optimization techniques and ways to avoid common performance pitfalls. In the end, you'll be prepared to build the algorithms and data structures most commonly encountered in day-to-day software development. What you will learn from this book The basics of algorithms, such as iteration and recursion Elementary data structures such as lists, stacks, and queues Basic and advanced sorting algorithms including insertion sort, quicksort, and shell sort Advanced data structures such as binary trees, ternary trees, and heaps Algorithms for string searching, string matching, hashing, and computational geometry How to use test-driven development techniques to ensure your code works as intended How to dramatically improve the performance of your code with hands-on techniques for profiling and optimization Who this book is for This book is for anyone who develops applications, or is just beginning to do so, and is looking to understand algorithms and data structures. An understanding of computer programming is beneficial. Wrox Beginning guides are crafted to make learning programming languages and technologies easier than you think, providing a structured, tutorial format that will guide you through all the techniques involved.


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.


Algorithms Author Robert Sedgewick
ISBN-10 9780133799101
Release 2014-02-01
Pages 530
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This book is Part I of the fourth edition of Robert Sedgewick and Kevin Wayne’s Algorithms , the leading textbook on algorithms today, widely used in colleges and universities worldwide. Part I contains Chapters 1 through 3 of the book. The fourth edition of Algorithms surveys the most important computer algorithms currently in use and provides a full treatment of data structures and algorithms for sorting, searching, graph processing, and string processing -- including fifty algorithms every programmer should know. In this edition, new Java implementations are written in an accessible modular programming style, where all of the code is exposed to the reader and ready to use. The algorithms in this book represent a body of knowledge developed over the last 50 years that has become indispensable, not just for professional programmers and computer science students but for any student with interests in science, mathematics, and engineering, not to mention students who use computation in the liberal arts. The companion web site, contains An online synopsis Full Java implementations Test data Exercises and answers Dynamic visualizations Lecture slides Programming assignments with checklists Links to related material The MOOC related to this book is accessible via the "Online Course" link at The course offers more than 100 video lecture segments that are integrated with the text, extensive online assessments, and the large-scale discussion forums that have proven so valuable. Offered each fall and spring, this course regularly attracts tens of thousands of registrants. Robert Sedgewick and Kevin Wayne are developing a modern approach to disseminating knowledge that fully embraces technology, enabling people all around the world to discover new ways of learning and teaching. By integrating their textbook, online content, and MOOC, all at the state of the art, they have built a unique resource that greatly expands the breadth and depth of the educational experience.

Practical Analysis of Algorithms

Practical Analysis of Algorithms Author Dana Vrajitoru
ISBN-10 9783319098883
Release 2014-09-03
Pages 466
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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.

Real World Algorithms

Real World Algorithms Author Panos Louridas
ISBN-10 9780262035705
Release 2017-03-17
Pages 528
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An introduction to algorithms for readers with no background in advanced mathematics or computer science, emphasizing examples and real-world problems.

C Common Knowledge

C   Common Knowledge Author Stephen C. Dewhurst
ISBN-10 9780672333668
Release 2005-02-28
Pages 272
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What Every Professional C++ Programmer Needs to Know—Pared to Its Essentials So It Can Be Efficiently and Accurately Absorbed C++ is a large, complex language, and learning it is never entirely easy. But some concepts and techniques must be thoroughly mastered if programmers are ever to do professional-quality work. This book cuts through the technical details to reveal what is commonly understood to be absolutely essential. In one slim volume, Steve Dewhurst distills what he and other experienced managers, trainers, and authors have found to be the most critical knowledge required for successful C++ programming. It doesn’t matter where or when you first learned C++. Before you take another step, use this book as your guide to make sure you’ve got it right! This book is for you if You’re no “dummy,” and you need to get quickly up to speed in intermediate to advanced C++ You’ve had some experience in C++ programming, but reading intermediate and advanced C++ books is slow-going You’ve had an introductory C++ course, but you’ve found that you still can’t follow your colleagues when they’re describing their C++ designs and code You’re an experienced C or Java programmer, but you don’t yet have the experience to develop nuanced C++ code and designs You’re a C++ expert, and you’re looking for an alternative to answering the same questions from your less-experienced colleagues over and over again C++ Common Knowledge covers essential but commonly misunderstood topics in C++ programming and design while filtering out needless complexity in the discussion of each topic. What remains is a clear distillation of the essentials required for production C++ programming, presented in the author’s trademark incisive, engaging style.

Bad Choices

Bad Choices Author Ali Almossawi
ISBN-10 9780735222236
Release 2017-04-04
Pages 160
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The wildly popular author of Bad Arguments returns with a funny, smart introduction to algorithms—those perennially misunderstood, increasingly important problem-solving rules that can save you time and lead to better choices, every day. Why is Facebook so good at predicting what you like? How do you discover new music? What's the best way to sort your laundry? Readers around the world have embraced Ali Almossawi's whimsical illustrations—drawn by his collaborator Alejandro Giraldo—and his funny, clarifying explanations of complex subjects. In fewer than 200 pages, Almossawi demystifies a new topic of increasing relevance to our lives: algorithms. Bad Choices is a book for anyone who's looked at a given task and wondered if there was a better, faster way to get the task done. What's the best way to organize a grocery list? What's the secret to being more productive at work? How can we better express ourselves in 140-characters? Presenting us with alternative methods for tackling twelve different scenarios, Almossawi guides us to better choices that borrow from same systems that underline a computer word processor, a Google search engine, or a Facebook ad. Once you recognize what makes a method faster and more efficient, you'll become a more nimble, creative problem-solver, ready to face new challenges. Bad Choices will open the world of algorithms to all readers making this a perennial go-to for fans of quirky, accessible science books. From the Hardcover edition.

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.

Game Programming Algorithms and Techniques

Game Programming Algorithms and Techniques Author Sanjay Madhav
ISBN-10 9780133463231
Release 2013-12-16
Pages 352
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Game Programming Algorithms and Techniques is a detailed overview of many of the important algorithms and techniques used in video game programming today. Designed for programmers who are familiar with object-oriented programming and basic data structures, this book focuses on practical concepts that see actual use in the game industry. Sanjay Madhav takes a unique platform- and framework-agnostic approach that will help develop virtually any game, in any genre, with any language or framework. He presents the fundamental techniques for working with 2D and 3D graphics, physics, artificial intelligence, cameras, and much more. Each concept is illuminated with pseudocode that will be intuitive to any C#, Java, or C++ programmer, and has been refined and proven in Madhav’s game programming courses at the University of Southern California. Review questions after each chapter help solidify the most important concepts before moving on. Madhav concludes with a detailed analysis of two complete games: a 2D iOS side-scroller (written in Objective-Cusing cocos2d) and a 3D PC/Mac/Linux tower defense game (written in C# using XNA/ MonoGame). These games illustrate many of the algorithms and techniques covered in the earlier chapters, and the full source code is available at Coverage includes Game time management, speed control, and ensuring consistency on diverse hardware Essential 2D graphics techniques for modern mobile gaming Vectors, matrices, and linear algebra for 3D games 3D graphics including coordinate spaces, lighting and shading, z-buffering, and quaternions Handling today’s wide array of digital and analog inputs Sound systems including sound events, 3D audio, and digital signal processing Fundamentals of game physics, including collision detection and numeric integration Cameras: first-person, follow, spline, and more Artificial intelligence: pathfinding, state-based behaviors, and strategy/planning User interfaces including menu systems and heads-up displays Scripting and text-based data files: when, how, and where to use them Basics of networked games including protocols and network topology

Algorithms in a Nutshell

Algorithms in a Nutshell Author George T. Heineman
ISBN-10 9781491912997
Release 2016-03-22
Pages 390
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Creating robust software requires the use of efficient algorithms, but programmers seldom think about them until a problem occurs. This updated edition of Algorithms in a Nutshell describes a large number of existing algorithms for solving a variety of problems, and helps you select and implement the right algorithm for your needs—with just enough math to let you understand and analyze algorithm performance. With its focus on application, rather than theory, this book provides efficient code solutions in several programming languages that you can easily adapt to a specific project. Each major algorithm is presented in the style of a design pattern that includes information to help you understand why and when the algorithm is appropriate. With this book, you will: Solve a particular coding problem or improve on the performance of an existing solution Quickly locate algorithms that relate to the problems you want to solve, and determine why a particular algorithm is the right one to use Get algorithmic solutions in C, C++, Java, and Ruby with implementation tips Learn the expected performance of an algorithm, and the conditions it needs to perform at its best Discover the impact that similar design decisions have on different algorithms Learn advanced data structures to improve the efficiency of algorithms

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"

Algorithms Unlocked

Algorithms Unlocked Author Thomas H. Cormen
ISBN-10 9780262313230
Release 2013-03-01
Pages 240
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Have you ever wondered how your GPS can find the fastest way to your destination, selecting one route from seemingly countless possibilities in mere seconds? How your credit card account number is protected when you make a purchase over the Internet? The answer is algorithms. And how do these mathematical formulations translate themselves into your GPS, your laptop, or your smart phone? This book offers an engagingly written guide to the basics of computer algorithms. In Algorithms Unlocked, Thomas Cormen -- coauthor of the leading college textbook on the subject -- provides a general explanation, with limited mathematics, of how algorithms enable computers to solve problems. Readers will learn what computer algorithms are, how to describe them, and how to evaluate them. They will discover simple ways to search for information in a computer; methods for rearranging information in a computer into a prescribed order ("sorting"); how to solve basic problems that can be modeled in a computer with a mathematical structure called a "graph" (useful for modeling road networks, dependencies among tasks, and financial relationships); how to solve problems that ask questions about strings of characters such as DNA structures; the basic principles behind cryptography; fundamentals of data compression; and even that there are some problems that no one has figured out how to solve on a computer in a reasonable amount of time.