Introduction to Algorithms, fourth edition

I am one of the authors of this book. Because Amazon no longer provides a "Reply" button on reviews, I am writing this review to counter a point made in other reviews that say that the fourth edition of Introduction to Algorithms is essentially the same as the third edition.I know this book better than anyone else on the planet, and the fourth edition is NOT the same as the third edition. I can see where you might think that if you compare the tables of contents. Or instead you could read the preface of the fourth edition, where we lay out in detail the changes we made in the fourth edition in 23 distinct bullet points describing global changes throughout the book and specific changes to chapters and sections.We worked on the fourth edition for several years. We would not have needed to do that if it were just "the third edition with color." I heartily suggest that reviewers actually READ the book before passing judgement on whether it's the same as the third edition.[Apologies for giving 5 stars. I had to give an overall rating, and in my humble and biased opinion, yeah, it deserves 5 stars.]

I gave 5 stars to the 4th edition. The authors put a huge amount of effort to update the content, and this edition has full Python code. If I say "because I had the 3rd edition, so I give the 4th edition 1 star", what do you think? It doesn't make any sense, right? Or, if I say "I regret buying the 4th edition since it as good as the 3rd edition, so I give the 4th edition 1 star" - what an interesting logic! BTW, I bought the Kindle version in 2021. I don't know why Amazon doesn't recognize my purchase. I personally suggest reading the Kindle version on computer with a large screen. That's true, the bitmap images can be blurry.

Received my copy of the new edition today. The volume of the book remains same as before at least its not significantly different in size but the printing is better, the illustrations are in color (which IMO was a necessary feature that has been missing in all previous editions). The algorithms in the book are still in psuedocode language agnostic and not in python which i somehow had an impression will be used in this edition but i am glad it is not.

If you have the third edition, really no need to buy this one. If not, this one is better marginally.This new edition adds machine learning algorithms, but you probably already know them better than what presented in this new edition. If not, you probably will learn it better from a machine learning textbook rather than this one, such as Keven Murphy's probabilistic ML.

If you are expecting anything other than the third edition with color it may not be worthwhile buying another copy, but if that is what you want then it is worth buying another copy.

The product came in good condition, I have read a decent portion of the 3rd edition from my library, and the 4th came out so I decided to jump the gun and buy it.The book does get difficult at times, and I would say coming from some knowledge of proofs and already knowing some programming data structures and theory will help a lot. This is my goto algorithms book.

like everything !

In a nutshell, this book is fantastic but it’s a bit academically oriented and I wouldn’t necessarily recommend it for most professionals as a “go to” algorithms book.There’s “arguably” barely any changes since the previous edition so you almost might as well save yourself a buck on that end.

I gave 5 stars to the 4th edition. The authors put a huge amount of effort to update the content, and this edition has full Python code. If I say "because I had the 3rd edition, so I give the 4th edition 1 star", what do you think? It doesn't make any sense, right? Or, if I say "I regret buying the 4th edition since it as good as the 3rd edition, so I give the 4th edition 1 star" - what an interesting logic! BTW, I bought the Kindle version in 2021. I don't know why Amazon doesn't recognize my purchase. I personally suggest reading the Kindle version on computer with a large screen. That's true, the bitmap images can be blurry.

This book is an absolute gem. Every page is dripping with information that a student of computer science should absorb. Read it slowly and carefully because it looks like the authors have put in a tremendous amount of effort writing it making just the points necessary for a deep and broad understanding of the subject.For the reader:The book has math but don't be afraid. You can always skip the parts you don't understand and revisit them later when you have more dots connected. A second or third reading of the material always fills old holes in knowledge that we didn't think we had. After all, that is how we learn, or at least, I do.The color illustrations are excellent and a good visual aid to people who are visual learners. You might want to start there and work your way deeper as time permits. I've found that reading the book slowly gets me faster through the book, which is kind of incredible if I think about it. Slow down. Take your time.