Lecture 19: Dynamic Programming I: Fibonacci, Shortest Paths
Why Hacker News recommends it
Recommended as a clear introduction to dynamic programming from a well-regarded instructor.
What it is
Erik Demaine's MIT 6.006 lecture introducing dynamic programming through Fibonacci numbers and shortest paths. It covers memoization, subproblems and optimal substructure.
Recommended by 4 HN commenters across 4 different months, 2016 to 2021.
What Hacker News said
Recommends philippeback · 2016-08 · on “The Imposter's Handbook”
When you deal with large data sets (e.g. Hadoop/Spark...), BigO starts to hit badly. Dynamic Programming also requires you to have a clue about it. See [this video] for some cool explanations.
Recommends gbacon · 2019-04 · on “Graphical Introduction to Dynamic Programming”
You may also like a couple of lectures by Erik Demaine: Dynamic Programming I: Fibonacci, Shortest Paths [this video] Dynamic Programming II: Text Justification, Blackjack [LINK]
Recommends dehrmann · 2021-02 · on “Algorithms by Jeff Erickson”
I don't think I've ever been asked a DP problem in an interview, and only had to use it while programming once . That said, I liked the MIT lecture on it: [this video]
Recommends dominotw · 2021-04 · on “Dynamic Programming vs. Divide-and-Conquer (2018)”
> on interviews they want you to explicitly construct the array very often i.e. it's the different between hire and a strong hire exactly because @lru_cache is much easier are you serious? someone really asked you to "use array". Beyond stupid if they really did. > you can easily blow the stack for real production grade implementations using recursion recursive solution doesn't automatically mean using a the method stack. you can implement recursive solutions using explicit stack . > dynamic programming proper please. There is no "proper" dynamic programming. Please watch this MIT intro [this video] .