Coursera-Stanford-Greedy-Algorithms-Minimum-Spanning-Trees-and-Dynamic-Programming

KO | EN

gitlite — search

#python #react #typescript #llm #golang #machine-learning #macos #nodejs #windows #awesome #cli #vue #mcp #open-source

Coursera-Stanford-Greedy-Algorithms-Minimum-Spanning-Trees-and-Dynamic-Programming

(★ 39)

Notebook for quick search

Coursera-Stanford-Greedy-Algorithms-Minimum-Spanning-Trees-and-Dynamic-Programming 최신버젼 다운로드

최종 버전 다운로드 (.zip)

// repository documentation

Was this content helpful?

★ 0 (0 ratings)

# Coursera-Stanford-Greedy-Algorithms-Minimum-Spanning-Trees-and-Dynamic-Programming

Course can be found in [Coursera](https://www.coursera.org/learn/algorithms-greedy)

Quiz answers and notebook for quick search can be found in my blog [SSQ](https://ssq.github.io/2017/07/17/Coursera%20S%20Algorithms%20Specialization%20Notebook/)

- Week 1: 
  - [Greedy algorithm](https://github.com/SSQ/Coursera-Stanford-Greedy-Algorithms-Minimum-Spanning-Trees-and-Dynamic-Programming/blob/master/Lecture%20Slides/19.2-algo2-greedy-sched2-typed.pdf);
  - [Prim's Minimum Spanning Tree](https://github.com/SSQ/Coursera-Stanford-Greedy-Algorithms-Minimum-Spanning-Trees-and-Dynamic-Programming/blob/master/Lecture%20Slides/20.2-algo2-greedy-mst2-typed.pdf);
  - [x] [Implementation](https://github.com/SSQ/Coursera-Stanford-Greedy-Algorithms-Minimum-Spanning-Trees-and-Dynamic-Programming/tree/master/Programming%20Assignment%201) based on jupyter notebook.
- Week 2: 
  - [Kruskal's MST algorithm](https://github.com/SSQ/Coursera-Stanford-Greedy-Algorithms-Minimum-Spanning-Trees-and-Dynamic-Programming/blob/master/Lecture%20Slides/21.1-algo2-greedy-kruskal1-typed.pdf);
  - applications to [clustering](https://github.com/SSQ/Coursera-Stanford-Greedy-Algorithms-Minimum-Spanning-Trees-and-Dynamic-Programming/blob/master/Lecture%20Slides/22.1-algo2-greedy-kruskal5-typed.pdf);
  - [ ] [Implementation]() based on jupyter notebook;
  - advanced union-find (optional).
- Week 3: 
  - [Huffman's Algorithm](https://github.com/SSQ/Coursera-Stanford-Greedy-Algorithms-Minimum-Spanning-Trees-and-Dynamic-Programming/blob/master/Lecture%20Slides/24.3-algo2-greedy-huffman3-typed.pdf); 
  - introduction to dynamic programming ([max weight](https://github.com/SSQ/Coursera-Stanford-Greedy-Algorithms-Minimum-Spanning-Trees-and-Dynamic-Programming/blob/master/Lecture%20Slides/25.3-algo2-dp-wis3-typed.pdf) [independent set](https://github.com/SSQ/Coursera-Stanford-Greedy-Algorithms-Minimum-Spanning-Trees-and-Dynamic-Programming/blob/master/Lecture%20Slides/25.4-algo2-dp-wis4-typed.pdf));
  - [x] [Implementation](https://github.com/SSQ/Coursera-Stanford-Greedy-Algorithms-Minimum-Spanning-Trees-and-Dynamic-Programming/tree/master/Programming%20Assignment%203) based on jupyter notebook.
- Week 4:
  - [Knapsack Algorithm](https://github.com/SSQ/Coursera-Stanford-Greedy-Algorithms-Minimum-Spanning-Trees-and-Dynamic-Programming/blob/master/Lecture%20Slides/26.2-algo2-dp-knapsack2-typed.pdf);
  - [x] [Implementation](https://github.com/SSQ/Coursera-Stanford-Greedy-Algorithms-Minimum-Spanning-Trees-and-Dynamic-Programming/tree/master/Programming%20Assignment%204) based on jupyter notebook;
  - [Sequence alignment](https://github.com/SSQ/Coursera-Stanford-Greedy-Algorithms-Minimum-Spanning-Trees-and-Dynamic-Programming/blob/master/Lecture%20Slides/27.2-algo2-dp-alignment2-typed.pdf);
  - [Optimal binary search trees](https://github.com/SSQ/Coursera-Stanford-Greedy-Algorithms-Minimum-Spanning-Trees-and-Dynamic-Programming/blob/master/Lecture%20Slides/28.4-algo2-dp-bst3-typed.pdf).

Coursera-Stanford-Greedy-Algorithms-Minimum-Spanning-Trees-and-Dynamic-Programming

Coursera-Stanford-Greedy-Algorithms-Minimum-Spanning-Trees-and-Dynamic-Programming 최신버젼 다운로드

오늘의 추천 프로젝트

Was this content helpful?

Recent Feedback

Coursera-Stanford-Greedy-Algorithms-Minimum-Spanning-Trees-and-Dynamic-Programming

Coursera-Stanford-Greedy-Algorithms-Minimum-Spanning-Trees-and-Dynamic-Programming 최신버젼 다운로드

오늘의 추천 프로젝트

Was this content helpful?

Recent Feedback

Download README