Someone mentioned Grokking Algorithms by Aditya Y. Bhargava in one of the CS educator Facbeook groups. It looked interesting so I thought I'd give it a once over.
It's certainly an accessible book. Text mixed with cute line drawings, "hand written" text, diagrams and picture.s It reminded me of one of my favorite, most accessible Calculus books Who Was Fourier.
Overall I enjoyed the book but I'm not sure what its best audience is. If you look at the selection of topics, it's a little haphazard. It introduces Big-O notation, sescrion sort, and intro recursion all of which are covered prior to an algorithms course. It also introduces linked lists in what I felt was an early and arbitrary place but then neither gave any more than a theoretical overview nor came back to them later. On the other hand, when the author covers QuickSort he at one point compares it to a MergeSort as if that were covered as well. On the more advanced side, there are Hash Tables, Dijkstra's Aalgorithm, Dyanmic Programming, and a few teasers at the end.
The biggest downside of the book, to me, is that some of the topics seem to be great explanations of things as long as you already know them. The Linked List coverage is a great example of this. The author does a nice job relating Linked Lists to memory and how they are theoretically implemented under the hood. That said, unless you've already studied linked lists it probably isn't enough to go anywhere. This might be fine if you are to assume that the reader has already taken data structures but if that's the case, the linked list section is probably superflous.
Another point I noted was that some of the coverage is pretty standard but some is great. I wasn't very impressed by the recursion chapter nor the coverage of Dijkstra's algorithm. They were fine but nothing special. On the other hand, I very much liked the way Bhargava laid out and discussed Dynamic Programming. To me, that section alone is probably worth the book. I don't think it's enough for you to build a unit on Dyanamic Programming but the author provides a great way of developing and talking about the subject and gives some nice examples. I also like the way it builds from Greedy Algorithms.
To be fair, I read a couple of Amazon Reviews of the book and one reviewer loved the coverage of Dijkstra's algorithm so there is a lot of subjectivity here.
A couple of other minor points worth thinking about are math and rigor. One of the quotes on the back of the book states:
This book does the impossible: it makes math fun and easy!
I've got to disagree with this. The book doesn't take any traditionally difficult math and magically make it trivial. Rather the book has some examples where basic math can be used to great effect. In one section, Bhargava talks about classifiers and similarity scores using the Distance Formula. It's somewhat similar to what I do here. He's not making hard math easy but rather he's showing that basic math can be amazingly useful and you can do cool and powerful things with it. Nothing wrong with that. It's a great thing to do but it's not making hard math easy. The author also refers the reader to external references for more.
The other point I want to mention is rigor - this is bound to come up whenever a book tries to be accessible. While it's true that the author seems to fudge or simplify a definition here and there I didn't find any major problems and think that his choices in terms of langauge, rigor, and fudge factor are generally appropriate.
So bottom line - who is this book for and should you get it?
This is not a standalone algorithms book. You couldn't use it for a class by that name. The book mentions that it could be useful to a code school graduate and given the lack of consistency in what's covered in code schools that's probably a good recommendation. It gives some feel and flavor on a number of subjects, does nothing poorly and while it omits things that might be necessary, it does many things well.
To me, this is an ideal book as resource for a teacher looking to stretch their APCS-A or APCS-AB class or possibly for an advanced student.
I enjoyed the book. You probably will too.