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Algorithms

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Tackle computer science challenges with classic to modern algorithms in machine learning, software design, data systems, and cryptography
by Imran Ahmad

The ability to use algorithms to solve real-world problems is a must-have skill for any developer or programmer. This book will help you not only to develop the skills to select and use an algorithm to tackle problems in the real world but also to understand how it works.

You'll start with an introduction to algorithms and discover various algorithm design techniques, before exploring how to implement different types of algorithms, with the help of practical examples. As you advance, you'll learn about linear programming, page ranking, and graphs, and will then work with machine learning algorithms to understand the math and logic behind them.

Case studies will show you how to apply these algorithms optimally before you focus on deep learning algorithms and learn about different types of deep learning models along with their practical use.

You will also learn about modern sequential models and their variants, algorithms, methodologies, and architectures that are used to implement Large Language Models (LLMs) such as ChatGPT.

Finally, you'll become well versed in techniques that enable parallel processing, giving you the ability to use these algorithms for compute-intensive tasks.

By the end of this programming book, you'll have become adept at solving real-world computational problems by using a wide range of algorithms.

What you will learn

  • Design algorithms for solving complex problems
  • Become familiar with neural networks and deep learning techniques
  • Explore existing data structures and algorithms found in Python libraries
  • Implement graph algorithms for fraud detection using network analysis
  • Delve into state-of-the-art algorithms for proficient Natural Language Processing illustrated with real-world examples
  • Create a recommendation engine that suggests relevant movies to subscribers
  • Grasp the concepts of sequential machine learning models and their foundational role in the development of cutting-edge LLMs

Who this book is for

This computer science book is for programmers or developers who want to understand the use of algorithms for problem-solving and writing efficient code. Whether you are a beginner looking to learn the most used algorithms concisely or an experienced programmer looking to explore cutting-edge algorithms in data science, machine learning, and cryptography, you'll find this book useful. Python programming experience is a must, knowledge of data science will be helpful but not necessary.

Level Up Your Core Programming Skills
by Jay Wengrow

Algorithms and data structures are much more than abstract concepts. Mastering them enables you to write code that runs faster and more efficiently, which is particularly important for today’s web and mobile apps. Take a practical approach to data structures and algorithms, with techniques and real-world scenarios that you can use in your daily production code, with examples in JavaScript, Python, and Ruby. This new and revised second edition features new chapters on recursion, dynamic programming, and using Big O in your daily work.

Use Big O notation to measure and articulate the efficiency of your code, and modify your algorithm to make it faster. Find out how your choice of arrays, linked lists, and hash tables can dramatically affect the code you write. Use recursion to solve tricky problems and create algorithms that run exponentially faster than the alternatives. Dig into advanced data structures such as binary trees and graphs to help scale specialized applications such as social networks and mapping software. You’ll even encounter a single keyword that can give your code a turbo boost. Practice your new skills with exercises in every chapter, along with detailed solutions.

Use these techniques today to make your code faster and more scalable.

by Marcello La Rocca

As a software engineer, you’ll encounter countless programming challenges that initially seem confusing, difficult, or even impossible. Don’t despair! Many of these “new” problems already have well-established solutions.

Advanced Algorithms and Data Structures teaches you powerful approaches to a wide range of tricky coding challenges that you can adapt and apply to your own applications. Providing a balanced blend of classic, advanced, and new algorithms, this practical guide upgrades your programming toolbox with new perspectives and hands-on techniques.

Unlock Your Programming Potential
by Daniel Zingaro

Are you hitting a wall with data structures and algorithms? Whether you’re a student prepping for coding interviews or an independent learner, this book is your essential guide to efficient problem-solving in programming.

UNLOCK THE POWER OF DATA STRUCTURES & ALGORITHMS: Learn the intricacies of hash tables, recursion, dynamic programming, trees, graphs, and heaps. Become proficient in choosing and implementing the best solutions for any coding challenge.

REAL-WORLD, COMPETITION-PROVEN CODE EXAMPLES: The programs and challenges in this book aren’t just theoretical—they’re drawn from real programming competitions. Train with problems that have tested and honed the skills of coders around the world.

GET INTERVIEW-READY: Prepare yourself for coding interviews with practice exercises that help you think algorithmically, weigh different solutions, and implement the best choices efficiently.

WRITTEN IN C, USEFUL ACROSS LANGUAGES: The code examples are written in C and designed for clarity and accessibility to those familiar with languages like C++, Java, or Python. If you need help with the C code, no problem: We’ve got recommended reading, too.

Algorithmic Thinking is the complete package, providing the solid foundation you need to elevate your coding skills to the next level.

by Robert Sedgewick and Kevin Wayne

This fourth edition of Robert Sedgewick and Kevin Wayne’s Algorithms is the leading textbook on algorithms today and is widely used in colleges and universities worldwide. This book 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.

by Dzejla Medjedovic, Emin Tahirovic and Ines Dedovic

Massive modern datasets make traditional data structures and algorithms grind to a halt. This fun and practical guide introduces cutting-edge techniques that can reliably handle even the largest distributed datasets.

In Algorithms and Data Structures for Massive Datasets you will learn:

  • Probabilistic sketching data structures for practical problems
  • Choosing the right database engine for your application
  • Evaluating and designing efficient on-disk data structures and algorithms
  • Understanding the algorithmic trade-offs involved in massive-scale systems
  • Deriving basic statistics from streaming data
  • Correctly sampling streaming data
  • Computing percentiles with limited space resources

Algorithms and Data Structures for Massive Datasets reveals a toolbox of new methods that are perfect for handling modern big data applications. You’ll explore the novel data structures and algorithms that underpin Google, Facebook, and other enterprise applications that work with truly massive amounts of data. These effective techniques can be applied to any discipline, from finance to text analysis. Graphics, illustrations, and hands-on industry examples make complex ideas practical to implement in your projects—and there’s no mathematical proofs to puzzle over. Work through this one-of-a-kind guide, and you’ll find the sweet spot of saving space without sacrificing your data’s accuracy.

by John Canning, Alan Broder and Robert Lafore

This practical introduction to data structures and algorithms can help every programmer who wants to write more efficient software. Building on Robert Lafores legendary Java-based guide, this book helps you understand exactly how data structures and algorithms operate. Youll learn how to efficiently apply them with the enormously popular Python language and scale your code to handle todays big data challenges.

Throughout, the authors focus on real-world examples, communicate key ideas with intuitive, interactive visualizations, and limit complexity and math to what you need to improve performance. Step-by-step, they introduce arrays, sorting, stacks, queues, linked lists, recursion, binary trees, 2-3-4 trees, hash tables, spatial data structures, graphs, and more. Their code examples and illustrations are so clear, you can understand them even if youre a near-beginner, or your experience is with other procedural or object-oriented languages.

  • Build core computer science skills that take you beyond merely writing code
  • Learn how data structures make programs (and programmers) more efficient
  • See how data organization and algorithms affect how much you can do with todays, and tomorrows, computing resources
  • Develop data structure implementation skills you can use in any language
  • Choose the best data structure(s) and algorithms for each programming problemand recognize which ones to avoid

Data Structures & Algorithms in Python is packed with examples, review questions, individual and team exercises, thought experiments, and longer programming projects. It’s ideal for both self-study and classroom settings, and either as a primary text or as a complement to a more formal presentation.

by Michael T. Goodrich, Roberto Tamassia and David M. Mount

An updated, innovative approach to data structures and algorithms

Written by an author team of experts in their fields, this authoritative guide demystifies even the most difficult mathematical concepts so that you can gain a clear understanding of data structures and algorithms in C++.

The unparalleled author team incorporates the object-oriented design paradigm using C++ as the implementation language, while also providing intuition and analysis of fundamental algorithms.

  • Offers a unique multimedia format for learning the fundamentals of data structures and algorithms
  • Allows you to visualize key analytic concepts, learn about the most recent insights in the field, and do data structure design
  • Provides clear approaches for developing programs
  • Features a clear, easy-to-understand writing style that breaks down even the most difficult mathematical concepts

Building on the success of the first edition, this new version offers you an innovative approach to fundamental data structures and algorithms.

by Michael T. Goodrich and Roberto Tamassia

The design and analysis of efficient data structures has long been recognized as a key component of the Computer Science curriculum. Goodrich, Tomassia and Goldwasser's approach to this classic topic is based on the object-oriented paradigm as the framework of choice for the design of data structures. For each ADT presented in the text, the authors provide an associated Java interface. Concrete data structures realizing the ADTs are provided as Java classes implementing the interfaces. The Java code implementing fundamental data structures in this book is organized in a single Java package, net.datastructures. This package forms a coherent library of data structures and algorithms in Java specifically designed for educational purposes in a way that is complimentary with the Java Collections Framework.

An Amusing Adventure with Coffee-Filled Examples
by Jeremy Kubica

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. Through diagrams, pseudocode, and humorous analogies, you’ll learn how the structure of data drives algorithmic operations, gaining insight into not just how to build data structures, but precisely how and when to use them.

This book will give you a strong background in implementing and working with more than 15 key data structures, from stacks, queues, and caches to bloom filters, skip lists, and graphs. Master linked lists by standing in line at a cafe, hash tables by cataloging the history of the summer Olympics, and Quadtrees by neatly organizing your kitchen cabinets. Along with basic computer science concepts like recursion and iteration, you’ll learn:

  • The complexity and power of pointers
  • The branching logic of tree-based data structures
  • How different data structures insert and delete data in memory
  • Why mathematical mappings and randomization are useful
  • How to make tradeoffs between speed, flexibility, and memory usage

Data Structures the Fun Way shows how to efficiently apply these ideas to real-world problems—a surprising number of which focus on procuring a decent cup of coffee. At any level, fully understanding data structures will teach you core skills that apply across multiple programming languages, taking your career to the next level.

A Pythonic Adventure for the Intrepid Beginner
by Bradford Tuckfield

Dive Into Algorithms is a wide-ranging, Pythonic tour of many of the world's most interesting algorithms. With little more than a bit of computer programming experience and basic high-school math, you'll explore standard computer science algorithms for searching, sorting, and optimization; human-based algorithms that help us determine how to catch a baseball or eat the right amount at a buffet; and advanced algorithms like ones used in machine learning and artificial intelligence. You'll even explore how ancient Egyptians and Russian peasants used algorithms to multiply numbers, how the ancient Greeks used them to find greatest common divisors, and how Japanese scholars in the age of samurai designed algorithms capable of generating magic squares.

You'll explore algorithms that are useful in pure mathematics and learn how mathematical ideas can improve algorithms. You'll learn about an algorithm for generating continued fractions, one for quick calculations of square roots, and another for generating seemingly random sets of numbers.

You'll also learn how to:

  • Use algorithms to debug code, maximize revenue, schedule tasks, and create decision trees
  • Measure the efficiency and speed of algorithms
  • Generate Voronoi diagrams for use in various geometric applications
  • Use algorithms to build a simple chatbot, win at board games, or solve sudoku puzzles
  • Write code for gradient ascent and descent algorithms that can find the maxima and minima of functions
  • Use simulated annealing to perform global optimization
  • Build a decision tree to predict happiness based on a person's characteristics

Once you've finished this book you'll understand how to code and implement important algorithms as well as how to measure and optimize their performance, all while learning the nitty-gritty details of today's most powerful algorithms.

Store, manipulate, and access data effectively and boost the performance of your applications
by Dr. Basant Agarwal

Choosing the right data structure is pivotal to optimizing the performance and scalability of applications. This new edition of Hands-On Data Structures and Algorithms with Python will expand your understanding of key structures, including stacks, queues, and lists, and also show you how to apply priority queues and heaps in applications. You'll learn how to analyze and compare Python algorithms, and understand which algorithms should be used for a problem based on running time and computational complexity. You will also become confident organizing your code in a manageable, consistent, and scalable way, which will boost your productivity as a Python developer.

By the end of this Python book, you'll be able to manipulate the most important data structures and algorithms to more efficiently store, organize, and access data in your applications.

What you will learn

  • Understand common data structures and algorithms using examples, diagrams, and exercises
  • Explore how more complex structures, such as priority queues and heaps, can benefit your code
  • Implement searching, sorting, and selection algorithms on number and string sequences
  • Become confident with key string-matching algorithms
  • Understand algorithmic paradigms and apply dynamic programming techniques
  • Use asymptotic notation to analyze algorithm performance with regard to time and space complexities
  • Write powerful, robust code using the latest features of Python

Who this book is for

This book is for developers and programmers who are interested in learning about data structures and algorithms in Python to write complex, flexible programs. Basic Python programming knowledge is expected.

A Programmer's Guide to Writing Better Code
by George Heineman

When it comes to writing efficient code, every software professional needs to have an effective working knowledge of algorithms. In this practical book, author George Heineman (Algorithms in a Nutshell) provides concise and informative descriptions of key algorithms that improve coding. Software developers, testers, and maintainers will discover how algorithms solve computational problems creatively.

Each chapter builds on earlier chapters through eye-catching visuals and a steady rollout of essential concepts, including an algorithm analysis to classify the performance of every algorithm presented in the book. At the end of each chapter, you'll get to apply what you've learned to a novel challenge problem -- simulating the experience you might find in a technical code interview.

With this book, you will:

  • Examine fundamental algorithms central to computer science and software engineering
  • Learn common strategies for efficient problem solving — such as divide and conquer, dynamic programming, and greedy approaches
  • Analyze code to evaluate time complexity using big O notation
  • Use existing Python libraries and data structures to solve problems using algorithms
  • Understand the main steps of important algorithms
by Donald E. Knuth

This first volume in the series begins with basic programming concepts and techniques, then focuses more particularly on information structures–the representation of information inside a computer, the structural relationships between data elements and how to deal with them efficiently. Elementary applications are given to simulation, numerical methods, symbolic computing, software and system design. Dozens of simple and important algorithms and techniques have been added to those of the previous edition. The section on mathematical preliminaries has been extensively revised to match present trends in research.

An Algorithmic Tale of Crime, Conspiracy, and Computation
by Jeremy Kubica

Meet Frank Runtime. Disgraced ex-detective. Hard-boiled private eye. Search expert.

When a robbery hits police headquarters, it’s up to Frank Runtime and his extensive search skills to catch the culprits. In this detective story, you’ll learn how to use algorithmic tools to solve the case. Runtime scours smugglers’ boats with binary search, tails spies with a search tree, escapes a prison with depth-first search, and picks locks with priority queues. Joined by know-it-all rookie Officer Notation and inept tag-along Socks, he follows a series of leads in a best-first search that unravels a deep conspiracy. Each chapter introduces a thrilling twist matched with a new algorithmic concept, ending with a technical recap.

Perfect for computer science students and amateur sleuths alike, The CS Detective adds an entertaining twist to learning algorithms.

Follow Frank’s mission and learn:

  • The algorithms behind best-first and depth-first search, iterative deepening, parallelizing, binary search, and more
  • Basic computational concepts like strings, arrays, stacks, and queues
  • How to adapt search algorithms to unusual data structures
  • The most efficient algorithms to use in a given situation, and when to apply common-sense heuristic methods