THE VIDEO SHELF · dynamic programming
Lecture 19: Dynamic Programming I: Fibonacci, Shortest Paths
Erik Demaine's MIT 6.006 lecture introducing dynamic programming through Fibonacci numbers and shortest paths. It covers memoization, subproblems and optimal substructure.
Why HN readers recommended it
Recommended as a clear introduction to dynamic programming from a well-regarded instructor.
This is a summary from the source dataset, not an endorsement by Hacker News or the video creator.
Video & recommendation details
- Creator / channel
- MIT OpenCourseWare
- Topic
- dynamic programming
- Format
- lecture
- Level
- intro
- HN recommenders in dataset
- 4
- HN mentions in dataset
- 4
- Recommendation years in dataset
- 2016–2021
These counts and years describe the included Hacker News records; they are not YouTube views or the video’s publication date.
From the original HN conversations
Excerpts from the recorded comments. Follow each source for the full comment and surrounding discussion.
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 [VIDEO] for some cool explanations.
philippeback on Hacker News · 2016-08
In The Imposter's HandbookYou may also like a couple of lectures by Erik Demaine: Dynamic Programming I: Fibonacci, Shortest Paths [VIDEO] Dynamic Programming II: Text Justification, Blackjack [LINK]
gbacon on Hacker News · 2019-04
In Graphical Introduction to Dynamic ProgrammingI 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]
dehrmann on Hacker News · 2021-02
In Algorithms by Jeff Erickson
Summaries, classifications and recommendation records are from the HackerTube source dataset. Read about this library and its limitations.