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Introduction to Algorithms, Second Edition

Thomas H. Cormen · 1 HN comments
HN Books has aggregated all Hacker News stories and comments that mention "Introduction to Algorithms, Second Edition" by Thomas H. Cormen.
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Amazon Summary
The first edition won the award for Best 1990 Professional and Scholarly Book in Computer Science and Data Processing by the Association of American Publishers. PLEASE NOTE: This is the international student paperback edition of this book. The MIT Press does not have sales rights for this paperback edition in the US and Canada. Customers in the US and Canada must order the hardcover edition. There are books on algorithms that are rigorous but incomplete and others that cover masses of material but lack rigor. Introduction to Algorithms combines rigor and comprehensiveness. The book 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. The algorithms are described in English and in a pseudocode designed to be readable by anyone who has done a little programming. The explanations have been kept elementary without sacrificing depth of coverage or mathematical rigor. The first edition became the standard reference for professionals and a widely used text in universities worldwide. The second edition features new chapters on the role of algorithms, probabilistic analysis and randomized algorithms, and linear programming, as well as extensive revisions to virtually every section of the book. In a subtle but important change, loop invariants are introduced early and used throughout the text to prove algorithm correctness. Without changing the mathematical and analytic focus, the authors have moved much of the mathematical foundations material from Part I to an appendix and have included additional motivational material at the beginning.
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I know its not an online course and its a relatively massive tome, but I'd recommend just working through "Introduction to Algorithms" by Cormen/Leiserston/Rivest/Stein [1].

This book has great explanations and exercises for everything you could want to learn from the basics of sorting and algorithmic design and analysis, to graph algorithms, linear programming, and dynamic programming.

It lacks some degree of depth on more advanced topics, but if you work your way through it and actually implement what you read and do the exercises, you will be more than well enough equipped to take on just about any problem.

The key is going to be to actually implement what you read/learn, I think it might take you a little more time than watching an online course, but in the long run it will give you a much deeper knowledge of the material.

1. https://www.amazon.com/Introduction-Algorithms-Thomas-H-Corm...

⬐ siteshwar
Video lectures from MIT course with same name are available here[1]. Few lectures are given by Leiserson, who is one of the authors of this book.

[1] http://videolectures.net/mit6046jf05_introduction_algorithms...

⬐ zombieprocess
Isn't this book too academical for any practical learning of algorithms and data structures?

I would recommend The algorithm design manual for more practical purposes. https://www.amazon.com/Algorithm-Design-Manual-Steven-Skiena...

⬐ rudedogg
His lectures from 2016 are also on YouTube: https://www.youtube.com/watch?v=A2bFN3MyNDA&list=PLOtl7M3yp-...
⬐ jfaucett
> Isn't this book too academical for any practical learning of algorithms and data structures?

I don't think so, I've worked through it and I didn't find it that difficult/academic. But I actually don't read a lot of computer science books / textbooks so I don't really have much to compare it to other than mathematical texts which I do read a lot of.

If you don't like proofs or math then its probably not the best text to work through, on the other hand, if you like rigorously understanding the material I would highly recommend it.

Either way, from what I remember it gives psuedocode for just about everything and has lots of graphs and pictures for elucidating the material, so you could probably just skip the math if you have an allergy to corrolaries, theorems, and proofs. Admittedly, that extra insight is probably a lot of the reason I liked it so much.

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