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Can you suggest any resources to freshen up on big o notation and fundamental data structures & algorithms that are not academically dense (i.e CLRS)? I'm curr
by fspear 10y ago
Can you suggest any resources to freshen up on big o notation and fundamental data structures & algorithms that are not academically dense (i.e CLRS)?
I'm currently working through Cracking the coding interview & Elements of programming interviews but I really need to revisit the fundamentals, specially recurrence relations and calculating the order of complexity for an algorithm but I can't find any resources that are not too academically verbose, I have a really hard time reading mathematical notation.
- lil1729 10y agoThe Stanford/Coursera course on algorithms part 1 is a good resource for Big O. Knuth's "Concrete mathematics", 9th chapter (I think) has some good coverage on Big-O/Omega notation.
- thalesfc 10y agoThis is my personal recommendation, please notice that I have read "Introduction to Algorithm by Cormen" about 4 years ago, so for me everything was more a catch up than really learning: - Skiena algorithm book: https://www.amazon.com/Algorithm-Design-Manual-Steve-Skiena/dp/0387948600/ref=nav_signin?s=books&ie=UTF8&qid=1471460903&sr=1-5&keywords=the+algorithm+design+manual& https://www.amazon.com/Algorithm-Design-Manual-Steve-Skiena/... for this book one can focuses on the first 7 chapters (revision) - Leet code editorial solutions https://leetcode.com/articles/ https://leetcode.com/articles/ . They provide with the solution and complexity analysis of a few problems. I suggest you try to solve and give your complexity analysis then compare it with the "official" one.