There are many distinct pleasures associated with computer programming. Craftsmanship has its quiet rewards, the satisfaction that comes from building a useful object and making it work. Excitement arrives with the flash of insight that cracks a previously intractable problem. The spiritual quest for elegance can turn the hacker into an artist. There are pleasures in parsimony, in squeezing the last drop of performance out of clever algorithms and tight coding. The games, puzzles, and challenges of problems from international programming competitions are a great way to experience these pleasures while improving your algorithmic and coding skills. This book contains over 100 problems that have appeared in previous programming contests, along with discussions of the theory and ideas necessary to attack them. Instant online grading for all of these problems is available from two WWW robot judging sites. Combining this book with a judge gives an exciting new way to challenge and improve your programming skills. This book can be used for self-study, for teaching innovative courses in algorithms and programming, and in training for international competition. The problems in this book have been selected from over 1,000 programming problems at the Universidad de Valladolid online judge. The judge has ruled on well over one million submissions from 27,000 registered users around the world to date. We have taken only the best of the best, the most fun, exciting, and interesting problems available.

Programming Challenges: The Programming Contest Training Manual (Texts in Computer Science)

Computers & Technology

Skiena, Steven S.

Games & Strategy Guides

Springer

Calculated Bets describes a gambling system that works. Steven Skiena, a jai-alai enthusiast and computer scientist, documents how he used computer simulations and modeling techniques to predict the outcome of jai-alai matches and increased his initial stake by 544% in one year. Skiena demonstrates how his jai-alai system functions like a stock trading system, and includes examples of how gambling and mathematics interact in program trading systems, how mathematical models are used in political polling, and what the future holds for Internet gambling. With humor and enthusiasm, Skiena explains computer predictions used in business, sports, and politics, and the difference between correlation and causation. An unusual presentation of how mathematical models are designed, built, and validated, Calculated Bets also includes a list of modeling projects with online data sources. Steven Skiena, Associate Professor of Computer Science at SUNY Stony Brook, is the author of The Algorithm Design Manual (Springer-Verlag, 1997) and the EDUCOM award-winning Computational Discrete Mathematics. He is the recipient of the ONR Young Investigator's Award and the Chancellor's Award for Excellence in Teaching at Stony Brook. His research interests include discrete mathematics and its applications, particularly the design of graph, string, and geometric algorithms.

Calculated Bets: Computers, Gambling, and Mathematical Modeling to Win (Outlooks)

Computer Science

The Mathematical Association of America

Amazon.com Review\nYou could just as easily call this book How to Bet at Jai-Alai and Win! But that's only half the story. While Calculated Bets might indeed help you make a buck down at the fronton, it's as much concerned with the power of mathematical modeling and computer programming. The story of accomplished mathematician Steven Skiena's longtime obsession with this obscure Basque sport, Calculated Bets uses straightforward mathematics and real-world examples to divine the statistical mysteries behind playing--and, more important, wagering on--jai alai. (Which goes a long way toward explaining why Cambridge University Press is publishing what's basically a book about gambling.) 
A self-styled "mild-mannered professor," the conversational Skiena (The Algorithm Design Manual) delivers on his book's many promises, from explaining how mathematical models are "designed, built, and validated" to providing lucid discussions of such topics as market efficiency and the difference between correlation and causation. Even better are his riffs on why real programmers hate Microsoft (hint: it's not jealousy) and the beauty behind interesting curves. In the end, Skiena even puts his money where his mouth is: using a modem, he sets loose an auto-dialing program called Maven that he and his grad students cooked up, sending it off in the wee hours of the morning to cull the Web for stats, play each match a half-million times, and then automatically wager a $250 stake. --Paul Hughes\nCalculated Bets describes a gambling system that works. Steven Skiena, a jai-alai enthusiast and computer scientist, documents how he used computer simulations and modeling techniques to predict the outcome of jai-alai matches and increased his initial stake by 544% in one year. Skiena demonstrates how his jai-alai system functions like a stock trading system, and includes examples of how gambling and mathematics interact in program trading systems, how mathematical models are used in political polling, and what the future holds for Internet gambling. With humor and enthusiasm, Skiena explains computer predictions used in business, sports, and politics, and the difference between correlation and causation. An unusual presentation of how mathematical models are designed, built, and validated, Calculated Bets also includes a list of modeling projects with online data sources. Steven Skiena, Associate Professor of Computer Science at SUNY Stony Brook, is the author of The Algorithm Design Manual (Springer-Verlag, 1997) and the EDUCOM award-winning Computational Discrete Mathematics. He is the recipient of the ONR Young Investigator's Award and the Chancellor's Award for Excellence in Teaching at Stony Brook. His research interests include discrete mathematics and its applications, particularly the design of graph, string, and geometric algorithms.

Programming Challenges: The Programming Contest Training Manual

Revilla, Miguel A.

Programming

The Algorithm Design Manual

The Algorithm Design Manual (Texts in Computer Science)

"My absolute favorite for this kind of interview preparation is Steven Skiena’s The Algorithm Design Manual. More than any other book it helped me understand just how astonishingly commonplace … graph problems are -- they should be part of every working programmer’s toolkit. The book also covers basic data structures and sorting algorithms, which is a nice bonus. … every 1 – pager has a simple picture, making it easy to remember. This is a great way to learn how to identify hundreds of problem types." (Steve Yegge, Get that Job at Google) 
"Steven Skiena’s Algorithm Design Manual retains its title as the best and most comprehensive practical algorithm guide to help identify and solve problems. … Every programmer should read this book, and anyone working in the field should keep it close to hand. … This is the best investment … a programmer or aspiring programmer can make." (Harold Thimbleby, Times Higher Education) 
"It is wonderful to open to a random spot and discover an interesting algorithm. This is the only textbook I felt compelled to bring with me out of my student days.... The color really adds a lot of energy to the new edition of the book!" (Cory Bart, University of Delaware) 
"The is the most approachable book on algorithms I have." (Megan Squire, Elon University) 
--- 
This newly expanded and updated third edition of the best-selling classic continues to take the "mystery" out of designing algorithms, and analyzing their efficiency. It serves as the primary textbook of choice for algorithm design courses and interview self-study, while maintaining its status as the premier practical reference guide to algorithms for programmers, researchers, and students.\nThe reader-friendly Algorithm Design Manual provides straightforward access to combinatorial algorithms technology, stressing design over analysis. The first part, Practical Algorithm Design, provides accessible instruction on methods for designing and analyzing computer algorithms. The second part, the Hitchhiker's Guide to Algorithms, is intended for browsing and reference, and comprises the catalog of algorithmic resources, implementations, and an extensive bibliography.\nNEW to the third edition: 
-- New and expanded coverage of randomized algorithms, hashing, divide and conquer, approximation algorithms, and quantum computing 
-- Provides full online support for lecturers, including an improved website component with lecture slides and videos 
-- Full color illustrations and code instantly clarify difficult concepts 
-- Includes several new "war stories" relating experiences from real-world applications 
-- Over 100 new problems, including programming-challenge problems from LeetCode and Hackerrank. 
-- Provides up-to-date links leading to the best implementations available in C, C++, and Java\nAdditional Learning Tools: 
-- 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 
-- Exercises include "job interview problems" from major software companies 
-- Highlighted "take home lessons" emphasize essential concepts 
-- The "no theorem-proof" style provides a uniquely accessible and intuitive approach to a challenging subject 
-- Many algorithms are presented with actual code (written in C) -- Provides comprehensive references to both survey articles and the primary literature\nWritten by a well-known algorithms researcher who received the IEEE Computer Science and Engineering Teaching Award, this substantially enhanced third edition of The Algorithm Design Manual is an essential learning tool for students and professionals needed a solid grounding in algorithms. Professor Skiena is also the author of the popular Springer texts, The Data Science Design Manual and Programming Challenges: The Programming Contest Training Manual.

"My absolute favorite for this kind of interview preparation is Steven Skiena''s The Algorithm Design Manual. More than any other book it helped me understand just how astonishingly commonplace ... graph problems are -- they should be part of every working programmer''s toolkit. The book also covers basic data structures and sorting algorithms, which is a nice bonus. ... every 1 - pager has a simple picture, making it easy to remember. This is a great way to learn how to identify hundreds of problem types." (Steve Yegge, Get that Job at Google) "Steven Skiena''s Algorithm Design Manual retains its title as the best and most comprehensive practical algorithm guide to help identify and solve problems. ... Every programmer should read this book, and anyone working in the field should keep it close to hand. ... This is the best investment ... a programmer or aspiring programmer can make." (Harold Thimbleby, Times Higher Education) "It is wonderful to open to a random spot and discover an interesting algorithm. This is the only textbook I felt compelled to bring with me out of my student days.... The color really adds a lot of energy to the new edition of the book!" (Cory Bart, University of Delaware) "The is the most approachable book on algorithms I have."&nbsp; &nbsp;(Megan Squire, Elon University) --- This newly expanded and updated third edition of the best-selling classic continues to take the "mystery" out of designing algorithms, and analyzing their efficiency.&nbsp; It serves as the primary textbook of choice for algorithm design courses and interview self-study, while maintaining its status as the premier practical reference guide to algorithms for programmers, researchers, and students. &nbsp; The reader-friendly&nbsp;Algorithm Design Manual&nbsp;provides straightforward access to combinatorial algorithms technology, stressing design over analysis.&nbsp; The first part, Practical Algorithm Design, provides accessible instruction on methods for designing and analyzing computer algorithms.&nbsp; The second part, the Hitchhiker''s Guide to Algorithms, is intended for browsing and reference, and comprises the catalog of algorithmic resources, implementations, and an extensive bibliography.&nbsp; NEW&nbsp;to the third edition:&nbsp; --&nbsp;New and expanded coverage&nbsp;of randomized algorithms, hashing, divide and conquer, approximation algorithms, and quantum computing&nbsp; -- Provides&nbsp;full online support&nbsp;for lecturers, including&nbsp;an improved website component&nbsp;with lecture slides and videos&nbsp; --&nbsp;Full color illustrations and code&nbsp;instantly clarify difficult concepts&nbsp; -- Includes several new "war stories"&nbsp;relating experiences from real-world applications &nbsp;-- Over&nbsp;100 new problems, including programming-challenge problems from LeetCode and Hackerrank.&nbsp; -- Provides&nbsp;up-to-date links&nbsp;leading to the best implementations available in C, C++, and Java &nbsp; Additional Learning Tools:&nbsp; -- 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&nbsp; -- Exercises include "job interview problems" from major software companies&nbsp; -- Highlighted "take home lessons" emphasize essential concepts&nbsp; -- The "no theorem-proof" style provides a uniquely accessible and intuitive approach to a challenging subject&nbsp; -- Many algorithms are presented with actual code (written in C)&nbsp; -- Provides comprehensive references to both survey articles and the primary literature &nbsp; Written by a well-known algorithms researcher who received the IEEE Computer Science and Engineering Teaching Award, this substantially enhanced third edition of&nbsp;The Algorithm Design Manual&nbsp;is an essential learning tool for students and professionals needed a solid grounding in algorithms.&nbsp;&nbsp; Professor Skiena is also the author of the popular Springer texts,&nbsp;The Data Science Design Manual&nbsp;and&nbsp;Programming Challenges: The Programming Contest Training Manual.

The Data Science Design Manual (Texts in Computer Science)

This engaging and clearly written textbook/reference provides a must-have introduction to the rapidly emerging interdisciplinary field of data science. It focuses on the principles fundamental to becoming a good data scientist and the key skills needed to build systems for collecting, analyzing, and interpreting data. The Data Science Design Manual is a source of practical insights that highlights what really matters in analyzing data, and provides an intuitive understanding of how these core concepts can be used. The book does not emphasize any particular programming language or suite of data-analysis tools, focusing instead on high-level discussion of important design principles. This easy-to-read text ideally serves the needs of undergraduate and early graduate students embarking on an “Introduction to Data Science” course. It reveals how this discipline sits at the intersection of statistics, computer science, and machine learning, with a distinct heft and character of its own. Practitioners in these and related fields will find this book perfect for self-study as well. Additional learning tools: <ul>
<li>Contains “War Stories,” offering perspectives on how data science applies in the real world 
</li>
<li>Includes “Homework Problems,” providing a wide range of exercises and projects for self-study 
</li>
<li>Provides a complete set of lecture slides and online video lectures at www.data-manual.com 
</li>
<li>Provides “Take-Home Lessons,” emphasizing the big-picture concepts to learn from each chapter 
</li>
<li>Recommends exciting “Kaggle Challenges” from the online platform Kaggle 
</li>
<li>Highlights “False Starts,” revealing the subtle reasons why certain approaches fail 
</li>
<li>Offers examples taken from the data science television show “The Quant Shop” (www.quant-shop.com) 
</li>
</ul>

Business & Money

Industries

This engaging and clearly written textbook/reference provides a must-have introduction to the rapidly emerging interdisciplinary field of data science. It focuses on the principles fundamental to becoming a good data scientist and the key skills needed to build systems for collecting, analyzing, and interpreting data. The Data Science Design Manual is a source of practical insights that highlights what really matters in analyzing data, and provides an intuitive understanding of how these core concepts can be used. The book does not emphasize any particular programming language or suite of data-analysis tools, focusing instead on high-level discussion of important design principles. This easy-to-read text ideally serves the needs of undergraduate and early graduate students embarking on an “Introduction to Data Science” course. It reveals how this discipline sits at the intersection of statistics, computer science, and machine learning, with a distinct heft and character of its own. Practitioners in these and related fields will find this book perfect for self-study as well. Additional learning tools: Contains “War Stories,” offering perspectives on how data science applies in the real worldIncludes “Homework Problems,” providing a wide range of exercises and projects for self-studyProvides a complete set of lecture slides and online video lectures at www.data-manual.comProvides “Take-Home Lessons,” emphasizing the big-picture concepts to learn from each chapterRecommends exciting “Kaggle Challenges” from the online platform KaggleHighlights “False Starts,” revealing the subtle reasons why certain approaches failOffers examples taken from the data science television show “The Quant Shop” (www.quant-shop.com)

El medio perfecto para mejorar la destreza en la programación. El estudio de los múltiples desafíos que representan los problemas de los concursos internacionales es un camino eficiente para mejorar las habilidades en algorítmica y programación. Las compañías de informática utilizan problemas similares a los de los concursos para motivar el estudio de algoritmos, programación y otros temas de ciencias de la computación. El libro incluye más de 100 problemas organizados por temas y complementados con material de apoyo teórico y práctico. Los lectores aprenden a la vez los algoritmos y las técnicas de programar. Para esta edición se ha revisado la traducción de la terminología y se han corregido un importante número de erratas. Steven S. Skiena es profesor de ciencias de la computación en la Universidad de Stony Brook (Nueva York, EE.UU.) y es autor de varios libros ampliamente difundidos, entre otros The Algorithm Design Manual. En el año 2001 recibió el IEEE Computer Society Undergraduate Teaching Award. Miguel A. Revilla es profesor de algorítmica y matemática aplicada en la Universidad de Valladolid (España). Es el responsable del archivo de problemas del ICPC y el creador del juez automático Online Judge. En el año 2005 recibió el ICPC Joseph S. DeBlasi Outstanding Contribution Award.

Desafíos de programación: El manual de entrenamiento para concursos de programación (Spanish Edition)

OJ Books

See the best price to sell, buy, or rent books by Skiena, Steven S.. BookScouter helps to compare book prices from 25+ online bookstores and 30+ buyback vendors with a single search.

Books by Skiena, Steven S.

See the best price to sell, buy, or rent books by Skiena, Steven S.. BookScouter helps to compare book prices from 25+ online bookstores and 30+ buyback vendors with a single search.

Programming Challenges: The Programming Contest Training Manual (Texts in Computer Science)

Calculated Bets: Computers, Gambling, and Mathematical Modeling to Win (Outlooks)

Calculated Bets: Computers, Gambling, and Mathematical Modeling to Win (Outlooks)

Programming Challenges: The Programming Contest Training Manual

The Algorithm Design Manual

The Algorithm Design Manual (Texts in Computer Science)

The Algorithm Design Manual (Texts in Computer Science)

The Data Science Design Manual (Texts in Computer Science)

The Data Science Design Manual (Texts in Computer Science)

Desafíos de programación: El manual de entrenamiento para concursos de programación (Spanish Edition)