Programmers
have to know about algorithms and computational math. These things come
in handy for a variety of purposes. In fact, most computer related
professionals have something to do with this field. So, with that in
mind, here are 16 of the best resources that we could find on
algorithms. |
1. Undergraduate and Introductory Graduate Courses on Algorithms: This is a compilation of links by Kirk Puhs, which will give you a lot of useful information on Algorithms.
2. A Computational Introduction to Number Theory and Algebra: This book, by Victor Shoup, contains all the basic concepts of computational number theory and algebra. It also includes the necessary mathematical background required.
3. Algorithms for programmers by Jörg Arndt: This is a pretty useful resource for those looking to learn about algorithms. Some of these will help beginners, while others will be suited for advanced students too.
4. Numerical Recipes in C and Fortran: This website contains various ebooks and allows you to read a particular number of pages for free every day. You can also get subscriptions for the books.
5. Numerical Methods lecture notes: These lecture notes by Stuart Dalziel will come in handy to anyone looking to gain knowledge in algorithms.
6. Algorithms and Complexity: Herbert S. Wilf's book on Algorithms and Complexity is another useful resource for understanding this topic.
7. East Side, West Side: These lecture notes by Herbert S. Wilf are useful in understanding "the generation of combinatorial objects and Maple programming that gets the job done."
8. Lecture Notes on Numerical Analysis: These lecture notes from Dennis Deturck and Herbert S. Wilf could be your ticket to becoming pros in algorithms.
9. Computer Algebra I and Computer Algebra II: Download these lecture notes by Joachim von zur Gathen and Jüergen Gerhard to your desktop and keep them there for whenever you need them.
10. The Stony Brook Algorithm Repository: Many have said that this book is all you need in order to understand combinatorial algorithms. Try it out!
13. An Annotated List of Selected NP - Complete Problems: This book is written by David Johnson, who also writes a column for the Journal of Algorithms.
14. A compendium of NP optimization problems: This compendium is a part of the book Complexity and Approximation.
15. Various notes by Ragesh Jaiswal: This lecture contains the following topics: Algebraic Structures, Probability Basics, Number Theory, Randomized Algorithms, Factoring Algorithms.
16. Graph Theory: These lecture notes by Tero Harju deals with Graph theory.
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