Processing ......
FreeComputerBooks.com
Links to Free Computer, Mathematics, Technical Books all over the World
 
Elementary Algorithms
🌠 Top Free Machine Learning Books - 100% Free or Open Source!
  • Title: Elementary Algorithms
  • Author(s) Xinyu Liu
  • Publisher: GitHub.com (December 29, 2021)
  • License(s): GNU General Public License Version 3
  • Hardcover/Paperback: N/A
  • eBook: PDF (503 pages)
  • Language: English and Chinese
  • ISBN-10: N/A
  • ISBN-13: N/A
  • Share This:  

Book Description

This is a free book about elementary algorithms and data structures. This book doesn't only focus on an imperative (or procedural) approach, but also includes purely functional algorithms and data structures.

It doesn't require readers to master any programming languages, because all the algorithms are described using mathematical functions and pseudocode.

There are plenty of books about algorithms, such as "Introduction to algorithms", "The art of computer programming", "structure and interpretation of computer programs", etc ... why another book? Is it reinvention of wheel?

This book can't compare with the above classic bibles at all. It has some features like:

  1. All algorithms are described in math formulas and pseudo codes. I hope it bring some taste of elegant by using algebraic symbols.
  2. All algorithms are realized in both purely functional and imperative approaches.
  3. The examples are provided in multiple programming languages, including C, Haskell, Python, C++, Scheme/Lisp. Haskell is the main language for all functional implementations.

In other words, this book teaches you how to think like a programmer - find the practical efficiency algorithms to solve your problems.

About the Authors
  • Xinyu Liu is a Software Developement Manager (SDM) at Amazon.
Reviews, Ratings, and Recommendations: Related Book Categories: Read and Download Links: Similar Books:
  • Algorithm Design (Jon Kleinberg, et al)

    This book introduces algorithms by looking at the real-world problems that motivate them. The book teaches a range of design and analysis techniques for problems that arise in computing applications.

  • Lecture Notes for the Algorithms (Jeff Erickson)

    This lecture notes 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. Each chapter is relatively self-contained and can be used as a unit of study.

  • Algorithms: Fundamental Techniques (Macneil Shonle, et al)

    The goal of the book is to show you how you can methodically apply different techniques to your own algorithms to make them more efficient. While this book mostly highlights general techniques, some well-known algorithms are also looked at in depth.

  • Algorithms, 4th Edition, by Robert Sedgewick and Kevin Wayne

    It surveys the most important algorithms and data structures in use today. Applications to science, engineering, and industry are a key feature of the book. We motivate each algorithm that we address by examining its impact on specific applications.

  • Algorithms and Data Structures (Niklaus Wirth)

    From the inventor of Pascal and Modula-2 comes a new version of Niklaus Wirth's classic work, Algorithms + Data Structure = Programs (PH, l975). It includes new material on sequential structure, searching and priority search trees.

  • The Algorithm Design Manual (Steven S. Skiena)

    This book serves as the primary textbook for any algorithm design course while maintaining its status as the premier practical reference guide to algorithms, intended as a manual on algorithm design for both students and computer professionals.

  • Introduction to Design Analysis of Algorithms (K. Raghava Rao)

    This book was very useful to easily understand the algorithms. This book is having enough examples on every algorithm. It has written for the sake of students to provide complete knowledge on Algorithms.

Book Categories
:
Other Categories
Resources and Links