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Lecture 19: Dynamic Programming I: Fibonacci, Shortest Paths

MIT OpenCourseWare · 2.9M views · 2013-01-14 · 51:47

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Overview

Erik Demaine's MIT 6.006 lecture introducing dynamic programming through Fibonacci numbers and shortest paths. It covers memoization, subproblems and optimal substructure.

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Recommended as a clear introduction to dynamic programming from a well-regarded instructor.

Recommended by 4 HN people across 4 months · HN mentions 2016–2021

Topics

Algorithms & data structuresUniversity lectures & courses
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algorithmsmemoizationshortest pathsmit ocwerik demaine

What people said

dominotw · 2021-04 · Recommendation

> 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 [VIDEO] .

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dehrmann · 2021-02 · Recommendation

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: [VIDEO]

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gbacon · 2019-04 · Recommendation

You may also like a couple of lectures by Erik Demaine: Dynamic Programming I: Fibonacci, Shortest Paths [VIDEO] Dynamic Programming II: Text Justification, Blackjack [LINK]

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