Grokking Algorithms
"Grokking Algorithms is a fully illustrated, friendly guide that teaches you how to apply common algorithms to the practical problems you face every day as a programmer. You'll start with sorting and searching and, as you build up your skills in thinking algorithmically, you'll tackle more complex concerns such as data compression and artificial intelligence. Each carefully presented example includes helpful diagrams and fully annotated code samples in Python."--Publisher's desription.
Stats for nerds
42recommend
75mentions
59people
2014–2025years
72% recommend27% neutral1% critical
Mentions per year
What Hacker News says
- Aditya Bhargava did it again. I have to say I am a fan already from the old days of Grokking Algorithms.
- Sedgewick's Algorithms book is great for practical learning but too tied to Java and implementation details. It is a bit shallow on theory, though the community and resources for other languages help.
That said, I personally prefer Introduction to Algorithms (CLRS) for its formal rigor and clear proofs, and Grokking Algorithms for building intuition.
The broader goal of this project is to build a well tested, reference quality set of implementations in C, Python, and Go. That is the next milestone.
- Not related to VPC, but I'm a big fan of the author. Loved his book "Grokking Algorithms: An Illustrated Guide for Programmers and Other Curious People" when it came out a few years ago. If you know anyone struggling with common data structures and algorithms, this book can make it fun for them.
- My Constraint Satisfaction lecture (https://www.youtube.com/watch?v=w5tPsbOvkmU) may help, though I will say it only serves as a light 75 minute overview of constraints. Specifically in the second half of the lecture I use girl scout cookies and scooters to try and explain Linear Programming.
A quick Googling pulled up a Linear Programming Using Excel tutorial: https://science.utm.my/procscimath/wp-content/uploads/sites/...
This type of problem was what helped me understand the optimizations. I haven't studied the inner workings of the Simplex method, but it is used in Excel's Solver as well as Apache Commons'.
While it is still computer science oriented, I also like Grokking Algorithms (https://www.manning.com/books/grokking-algorithms). I used it as a source when I was building out some examples when I was teaching Algorithmic analysis and data structures. It does a great job of distilling the problems into a beginner friendly way that will lead you to dig into "what libraries are out there that have implemented this?"
- For algorithms, I would recommend "Grokking Algorithms" by Aditya Y. Bhargava. The reason is that the book contains hand drawn visualization. I believe this will make the beginner easier to learn the concept.
One more thing, if you learn programming. Don't forget to practice, practice, and practice. The book has exercise sections. Please, don't skip it.
https://www.manning.com/books/grokking-algorithms-second-edi...
- For beginners, I can recommend Grokking Algorithms by Bhargava. Small book with lots of illustrations, which is good for building up an intuition of what's going on.
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