A comprehensive update of the leading algorithms text, with new material on matchings in bipartite graphs, online algorithms, machine learning, and other topics.Some books on algorithms are rigorous but incomplete; others cover masses of material but lack rigor. Introduction to Algorithms uniquely combines rigor and comprehensiveness. It covers a broad range of algorithms in depth, yet makes their design and analysis accessible to all levels of readers, with self-contained chapters and algorithms in pseudocode. Since the publication of the first edition, Introduction to Algorithms has become the leading algorithms text in universities worldwide as well as the standard reference for professionals. This fourth edition has been updated throughout.New for the fourth edition New chapters on matchings in bipartite graphs, online algorithms, and machine learningNew material on topics including solving recurrence equations, hash tables, potential functions, and suffix arrays140 new exercises and 22 new problemsReader feedback–informed improvements to old problemsClearer, more personal, and gender-neutral writing styleColor added to improve visual presentationNotes, bibliography, and index updated to reflect developments in the fieldWebsite with new supplementary materialWarning: Avoid counterfeit copies of Introduction to Algorithms by buying only from reputable retailers. Counterfeit and pirated copies are incomplete and contain errors. Read more

This book introduces the mathematics that supports advanced computer programming and the analysis of algorithms. The primary aim of its well-known authors is to provide a solid and relevant base of mathematical skills - the skills needed to solve complex problems, to evaluate horrendous sums, and to discover subtle patterns in data. It is an indispensable text and reference not only for computer scientists - the authors themselves rely heavily on it! - but for serious users of mathematics in virtually every discipline.Concrete Mathematics is a blending of CONtinuous and disCRETE mathematics. "More concretely," the authors explain, "it is the controlled manipulation of mathematical formulas, using a collection of techniques for solving problems." The subject matter is primarily an expansion of the Mathematical Preliminaries section in Knuth's classic Art of Computer Programming, but the style of presentation is more leisurely, and individual topics are covered more deeply. Several new topics have been added, and the most significant ideas have been traced to their historical roots. The book includes more than 500 exercises, divided into six categories. Complete answers are provided for all exercises, except research problems, making the book particularly valuable for self-study.Major topics include:SumsRecurrencesInteger functionsElementary number theoryBinomial coefficientsGenerating functionsDiscrete probabilityAsymptotic methodsThis second edition includes important new material about mechanical summation. In response to the widespread use of the first edition as a reference book, the bibliography and index have also been expanded, and additional nontrivial improvements can be found on almost every page. Readers will appreciate the informal style of Concrete Mathematics. Particularly enjoyable are the marginal graffiti contributed by students who have taken courses based on this material. The authors want to convey not only the importance of the techniques presented, but some of the fun in learning and using them. Read more

Accessible, no-nonsense, and programming language-agnostic introduction to algorithms. Includes solutions to all quizzes and selected problems, and a series of YouTube videos by the author accompanies the book. Part 1 covers asymptotic analysis and big-O notation, divide-and-conquer algorithms and the master method, randomized algorithms, and several famous algorithms for sorting and selection. Read more

This text, extensively class-tested over a decade at UC Berkeley and UC San Diego, explains the fundamentals of algorithms in a story line that makes the material enjoyable and easy to digest. Emphasis is placed on understanding the crisp mathematical idea behind each algorithm, in a manner that is intuitive and rigorous without being unduly formal. Features include: The use of boxes to strengthen the narrative: pieces that provide historical context, descriptions of how the algorithms are used in practice, and excursions for the mathematically sophisticated. Carefully chosen advanced topics that can be skipped in a standard one-semester course, but can be covered in an advanced algorithms course or in a more leisurely two-semester sequence. An accessible treatment of linear programming introduces students to one of the greatest achievements in algorithms. An optional chapter on the quantum algorithm for factoring provides a unique peephole into this exciting topic. In addition to the text, DasGupta also offers a Solutions Manual, which is available on the Online Learning Center. "Algorithms is an outstanding undergraduate text, equally informed by the historical roots and contemporary applications of its subject. Like a captivating novel, it is a joy to read." Tim Roughgarden Stanford University Read more

Learn how and when to use the right data structures in any situation, strengthening your computational thinking, problem-solving, and programming skills in the process.This accessible and entertaining book provides an in-depth introduction to computational thinking through the lens of data structures — a critical component in any programming endeavor. You’ll learn how to work with more than 15 key data structures, from stacks, queues, and caches to bloom filters, skip lists, and graphs. You’ll also master linked lists by virtually standing in line at a cafe, hash tables by cataloging the history of the summer Olympics, and Quadtrees by neatly organizing your kitchen cabinets, all while becoming familiar with basic computer science concepts, like recursion and running time analysis. Read more

DSA Takeover: Work smart, master Algorithms quickly and secure your dream FAANGMULA job.This book “Data Structures and Algorithms: Coding Cheatsheet: The DSA Takeover Edition” is the only book you need to master Data Structures and Algorithms coding problems.The plain truth is: This is a goldmine to help you take over the entire DSA knowledge.This book include:Chapters covering all core domains in Data Structures and AlgorithmsEach chapter is a CHEATSHEET. It includes time & space complexity table, to-the-point explanation and C++ code snippets.Each problem can be covered quickly in at most 4 minutes.Over 250 coding problems have been covered.With this, you will be able to crack any Coding Interview easily.After reading this book, you will:Master Data Structures and Algorithms.Clear interviews for full-time positions at high-tech companies (good enough for L3, L4 at Google).On going through this book, you do not need to solve 1000s of problems from Leetcode by spending over two years. Follow this book, practice the problems and ace every coding interview. Be wise.This book is for:Students and developers preparing for Coding Interviews.Developers who wanted to tune their Data Structures and Algorithms skills.Students who need a coding sheet to revise DSA topics quickly.Get started with this book and change the equation of your career.Book: Data Structures and Algorithms: Coding Cheatsheets: The DSA Takeover EditionAuthors (2): Aditya Chatterjee, Ue KiaoContributors (2): Toby Dobrzyniewicz, Geoffrey ZiskovinAbout the authors:Aditya Chatterjee is an Independent Researcher, Technical Author and the Founding Member of OPENGENUS, a scientific community focused on Computing Technology.Ue Kiao is a Japanese Software Developer and has played key role in designing systems like TaoBao, AliPay and many more. She has completed her B. Sc in Mathematics and Computing Science at National Taiwan University and PhD at Tokyo Institute of Technology.About the contributors:Toby Dobrzyniewicz is a Software Developer based in California and originally, from Poland. He has worked at Uber, Palantir and Hitachi over the last decade.Geoffrey Ziskovin is an American Software Engineer with an experience of over 30 years. He has interviewed over 700 candidates worldwide for various Fortune 500 companies.Published: 1st October 2024 (Edition 1.0)Updated on: 30th January 2025 (Edition 1.8)Pages: 298Publisher: © OpenGenusTable of contents:1. How to use DSA Takeover?2. CHEATSHEET: Search Algorithms3. CHEATSHEET: Selection Algorithms4. CHEATSHEET: Sorting Algorithms5. CHEATSHEET: Basic calculations6. CHEATSHEET: Arithmetic Operations (Complexity Analysis)7. CHEATSHEET: Exponentiation Algorithms8. CHEATSHEET: Recursion & Iterative algorithms9. VISUALIZE: Basic Data Structures10. CHEATSHEET: Array11. CHEATSHEET: Stack12. CHEATSHEET: Linked List13. CHEATSHEET: Greedy Algorithms14. CHEATSHEET: Dynamic Programming [DP]15. CHEATSHEET: Permutation Algorithms16. CHEATSHEET: Bitwise Algorithms17. CHEATSHEET: String Algorithms18. CHEATSHEET: Graph Algorithms19. CHEATSHEET: Crazy Hard Problems20. CONCLUDING NOTE Read more

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In Hacker’s Delight, Second Edition, Hank Warren once again compiles an irresistible collection of programming hacks: timesaving techniques, algorithms, and tricks that help programmers build more elegant and efficient software, while also gaining deeper insights into their craft. Warren’s hacks are eminently practical, but they’re also intrinsically interesting, and sometimes unexpected, much like the solution to a great puzzle. They are, in a word, a delight to any programmer who is excited by the opportunity to improve. Extensive additions in this edition include A new chapter on cyclic redundancy checking (CRC), including routines for the commonly used CRC-32 code A new chapter on error correcting codes (ECC), including routines for the Hamming code More coverage of integer division by constants, including methods using only shifts and adds Computing remainders without computing a quotient More coverage of population count and counting leading zeros Array population count New algorithms for compress and expand An LRU algorithm Floating-point to/from integer conversions Approximate floating-point reciprocal square root routine A gallery of graphs of discrete functions Now with exercises and answers . Read more

You know how to code......but is it enough?Do you feel left out when other programmers talk about asymptotic bounds?Have you failed a job interview because you don't know computer science?Volume one covers the most frequently referenced topics, including:- Algorithms and data structures- Graphs- Problem-solving techniques- Complexity theoryThe author, a senior developer at a major software company with a PhD in computer science, takes you through what you would have learned while earning a four-year computer science degree. When you finish this book, you'll have the tools you need to hold your own with people who have - or expect you to have - a computer science degree.You already know how to program. Don't let the lack of a degree hold back your career. Read more

Implementing cryptography requires integers of significant magnitude to resist cryptanalytic attacks. Modern programming languages only provide support for integers which are relatively small and single precision. The purpose of this text is to instruct the reader regarding how to implement efficient multiple precision algorithms.Bignum math is the backbone of modern computer security algorithms. It is the ability to work with hundred-digit numbers efficiently using techniques that are both elegant and occasionally bizarre. This book introduces the reader to the concept of bignum algorithms and proceeds to build an entire library of functionality from the ground up. Through the use of theory, pseudo-code and actual fielded C source code the book explains each and every algorithm that goes into a modern bignum library. Excellent for the student as a learning tool and practitioner as a reference alike BigNum Math is for anyone with a background in computer science who has taken introductory level mathematic courses. The text is for students learning mathematics and cryptography as well as the practioner who needs a reference for any of the algorithms documented within. Read more

This book explores the intuitive appeal of neural networks and the genetic algorithm in finance. It demonstrates how neural networks used in combination with evolutionary computation outperform classical econometric methods for accuracy in forecasting, classification and dimensionality reduction. McNelis utilizes a variety of examples, from forecasting automobile production and corporate bond spread, to inflation and deflation processes in Hong Kong and Japan, to credit card default in Germany to bank failures in Texas, to cap-floor volatilities in New York and Hong Kong.* Offers a balanced, critical review of the neural network methods and genetic algorithms used in finance * Includes numerous examples and applications * Numerical illustrations use MATLAB code and the book is accompanied by a website Read more

Accessible, no-nonsense, and programming language-agnostic introduction to algorithms. Includes hints or solutions to all quizzes and problems, and a series of YouTube videos by the author accompanies the book. Part 3 covers greedy algorithms (scheduling, minimum spanning trees, clustering, Huffman codes) and dynamic programming (knapsack, sequence alignment, shortest paths, optimal search trees). Read more

The Art of Computer Programming is a multivolume work on the analysis of algorithms and has long been recognized as the definitive description of classical computer science. The five volumes published to date--Volumes 1, 2, 3, 4A, and 4B--already comprise a unique and invaluable resource in programming theory and practice. Countless readers have spoken about the profound personal influence of Knuth's writings. Scientists have marveled at the beauty and elegance of his analysis, while practicing programmers have successfully applied his "cookbook" solutions to their day-to-day problems. All have admired Knuth for the breadth, clarity, accuracy, and good humor found in his books.To continue the set, and to update parts of the existing volumes, Knuth has created a series of small books called fascicles, which are published at regular intervals. Each fascicle encompasses a section or more of wholly new or revised material. Ultimately, the content of these fascicles will be rolled up into the comprehensive, final versions of each volume, and the enormous undertaking that began in 1962 will be complete.Volume 4, Fascicle 7, which is brimming with lively examples, forms the first third of what will eventually become hardcover Volume 4C. It introduces and explores an important general framework for modeling and solving combinatorial problems, called the Constraint Satisfaction Problem (CSP). The concluding sections of Volume 4B contain expositions of two analogous frameworks, namely XCC ("exact covering with colors") and SAT ("Boolean satisfiability"); the XCC solvers and SAT solvers are now joined by CSP solvers, completing a powerful trio of techniques. Each member of the trio has its own strengths, while separately helping to understand the other two.This fascicle illuminates how the CSP framework is tied to dozens of other parts of computer science: Scene analysis (computer vision); efficient algorithms that embed one graph in another; fascinating instances of "graceful graphs"; new ways to look ahead when backtracking; new heuristics to guide a search that backtracks through a massive space of possibilities; situations when backtracking isn't necessary.New sparse-set data structures are introduced, leading to a technique called "dancing cells"--which often is even better than "dancing links"! Recreational topics appear throughout, including some new takes on the classic problem of a knight's tour, as well as modern puzzles such as fillomino.Nearly 500 exercises are provided, arranged carefully for self-instruction, together with detailed answers (in fact, sometimes also with answers to the answers). All the while, the author pays significant attention to the history of the subject and its human dimensions. Read more

Now Includes the Long-Anticipated Volume 4B!Countless readers have spoken about the profound personal influence of Knuth's work. Scientists have marveled at the beauty and elegance of his analysis, while ordinary programmers have successfully applied his "cookbook" solutions to their day-to-day problems. All have admired Knuth for the breadth, clarity, accuracy, and good humor found in his books.Primarily written as a reference, some people have nevertheless found it possible and interesting to read each volume from beginning to end. A programmer in China even compared the experience to reading a poem. Whatever your background, if you need to do any serious computer programming, you will find your own good reason to make each volume in this series a readily accessible part of your scholarly or professional library.These five books comprise what easily could be the most important set of information on any serious programmer's bookshelf.This set now includes Volume 4B, the sequel to Volume 4A, which extends Knuth's exploration of combinatorial algorithms. These algorithms are of keen interest to software designers because ". . . a single good idea can save years or even centuries of computer time.""Donald Knuth may very well be a great master of the analysis of algorithms, but more than that, he is an incredible and tireless storyteller who always strikes the perfect balance between theory, practice, and fun. [The Art of Computer Programming, Volume 4B, Combinatorial Algorithms, Part 2,] dives deep into the fascinating exploration of search spaces (which is quite like looking for a needle in a haystack or, even harder, to prove the absence of a needle in a haystack), where actions performed while moving forward must be meticulously undone when backtracking. It introduces us to the beauty of dancing links for removing and restoring the cells of a matrix in a dance which is both simple to implement and very efficient. And it studies the iconic and versatile satisfiability problem and carefully analyses various ingredients of SAT solvers." --Christine Solnon, Department of Computer Science, INSA LyonThis box set includes the following volumes: The Art of Computer Programming: Volume 1: Fundamental Algorithms, 3rd EditionThe Art of Computer Programming, Volume 2: Seminumerical Algorithms, 3rd EditionThe Art of Computer Programming: Volume 3: Sorting and Searching, 2nd EditionThe Art of Computer Programming, Volume 4A: Combinatorial Algorithms, Part 1The Art of Computer Programming, Volume 4B: Combinatorial Algorithms, Part 2 Read more

Modeling in Economics and Finance with Mathematica is edited and partially authored by a well-known textbook book writer in Economics, Hal Varian, Dept. of Econ omics, U. of Michigan. His books published with W.W. Norton have enjoyed success for more than a decade. Varian now parlays that writing ability by coordinating the publication of this new contribution and adding it to the growing library of publications surrounding the phenomenal Mathematica software and mathematical computing system authored by Stephen Wolfram. Economists, stock brokers, budgeters and financial analysts have been asking for such a "hands on" package for years. This accessible, authoritative guide will be the solution they've been waiting for! Read more

Accessible, no-nonsense, and programming language-agnostic introduction to algorithms. Includes solutions to all quizzes and selected problems, and a series of YouTube videos by the author accompanies the book. Part 2 covers graph search and its applications, shortest-path algorithms, and the applications and implementation of several data structures: heaps, search trees, hash tables, and bloom filters. (Part 1 is not a prerequisite.) Read more

DescriptionMastering AI and ML algorithms is essential for data scientists. This book covers a wide range of techniques, from supervised and unsupervised learning to deep learning and reinforcement learning. This book is a compass to the most important algorithms that every data scientist should have at their disposal when building a new AI/ML application.This book offers a thorough introduction to AI and ML, covering key concepts, data structures, and various algorithms like linear regression, decision trees, and neural networks. It explores learning techniques like supervised, unsupervised, and semi-supervised learning and applies them to real-world scenarios such as natural language processing and computer vision. With clear explanations, code examples, and detailed descriptions of 40 algorithms, including their mathematical foundations and practical applications, this resource is ideal for both beginners and experienced professionals looking to deepen their understanding of AI and ML.The final part of the book gives an outlook for more state-of-the-art algorithms that will have the potential to change the world of AI and ML fundamentals.Key Features● Covers a wide range of AI and ML algorithms, from foundational concepts to advanced techniques.● Includes real-world examples and code snippets to illustrate the application of algorithms.● Explains complex topics in a clear and accessible manner, making it suitable for learners of all levels.What you will learn● Differences between supervised, unsupervised, and reinforcement learning.● Gain expertise in data cleaning, feature engineering, and handling different data formats.● Learn to implement and apply algorithms such as linear regression, decision trees, neural networks, and support vector machines.● Creating intelligent systems and solving real-world problems.● Learn to approach AI and ML challenges with a structured and analytical mindset.Who this book is forThis book is ideal for data scientists, ML engineers, and anyone interested in entering the world of AI.Table of Contents1. Fundamentals2. Typical Data Structures3. 40 AI/ML Algorithms Overview4. Basic Supervised Learning Algorithms5. Advanced Supervised Learning Algorithms6. Basic Unsupervised Learning Algorithms7. Advanced Unsupervised Learning Algorithms8. Basic Reinforcement Learning Algorithms9. Advanced Reinforcement Learning Algorithms10. Basic Semi-Supervised Learning Algorithms11. Advanced Semi-Supervised Learning Algorithms12. Natural Language Processing13. Computer Vision14. Large-Scale Algorithms15. Outlook into the Future: Quantum Machine Learning Read more

Algorithms are the lifeblood of computer science. They are the machines that proofs build and the music that programs play. Their history is as old as mathematics itself. This textbook is a wide-ranging, idiosyncratic treatise on the design and analysis of algorithms, covering several fundamental techniques, with an emphasis on intuition and the problem-solving process. The book includes important classical examples, hundreds of battle-tested exercises, far too many historical digressions, and exaclty four typos. Jeff Erickson is a computer science professor at the University of Illinois, Urbana-Champaign; this book is based on algorithms classes he has taught there since 1998. Read more

Explore the support Rust offers for creating Functional Applications in Rust, learn about various design patterns, implementing concurrency, metaprogramming etc. in the process.Key FeaturesLearn current state-of-the-art Functional techniques in Rust.Modularize your applications and make them highly reusable and testable using functional design patterns.Get familiar with complex concepts such as metaprogramming, concurrency, and immutabilityBook DescriptionFunctional programming allows developers to divide programs into smaller, reusable components that ease the creation, testing, and maintenance of software as a whole. Combined with the power of RUST, you can develop robust and scalable applications that fulfill modern day software requirements. This book will help you discover all the RUST features that can be applied to build software in a functional way.We begin with a brief comparison of functional and object-oriented approach to different problems and patterns. We then quickly look at patterns of control flow, data the abstractions of these unique to functional programming. The next part covers how to create functional apps in Rust; mutability and ownership which are exclusive to Rust are also discussed. Pure functions are examined next and we understand closures, the various types of closures and currying. We also look at implementing concurrency through functional design principles and metaprogramming using macros. Before wrapping up we look at best practices for debugging and optimization.By the end of the book, you will be familiar with the functional approach of programming and will be able to use these techniques on a daily basis.What you will learnSupport offered by Rust for the use of basic Functional Programming principles.Use Functional Programming to handle concurrency with safety and elegance. Read and interpret complex type signatures for types and functions.Implement powerful abstractions using meta programming in Rust.Create quality code formulaically using functional design patterns of Rust.Familiarize with Rust's complex ownership mechanisms, particularly in regards to mutability.Who This Book Is ForThe reader should be fairly proficient in Rust already, showing an ability to read and understand Rust code. The reader has an interest in further improving their coding abilities in Rust. "Functional Programming in RUST" will now inform these readers of slightly more advanced techniques to improve their skillset. Read more