https://github.com/rajgoesout/algorithms
Implementation of basic data structures & algorithms.
https://github.com/rajgoesout/algorithms
algorithm divide-and-conquer python
Last synced: 20 days ago
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Implementation of basic data structures & algorithms.
- Host: GitHub
- URL: https://github.com/rajgoesout/algorithms
- Owner: rajgoesout
- Created: 2018-08-06T12:48:09.000Z (almost 7 years ago)
- Default Branch: master
- Last Pushed: 2019-04-24T05:50:50.000Z (about 6 years ago)
- Last Synced: 2024-03-02T14:17:30.105Z (about 1 year ago)
- Topics: algorithm, divide-and-conquer, python
- Language: Python
- Size: 177 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Algorithms
Python implementation of algorithms from [CLRS](https://en.wikipedia.org/wiki/Introduction_to_Algorithms) book.
### Part 1: Divide and Conquer, Sorting and Searching, and Randomized Algorithms
Primary topics: asymptotic ("Big-oh") notation, sorting and searching, divide and conquer (master method, integer and matrix multiplication, closest pair), and randomized algorithms (QuickSort, contraction algorithm for min cuts).
### Part 2: Graph Search, Shortest Paths, and Data Structures
Primary topics: data structures (heaps, balanced search trees, hash tables, bloom filters), graph primitives (applications of breadth-first and depth-first search, connectivity, shortest paths), and their applications (ranging from deduplication to social network analysis).
### Part 3: Greedy Algorithms, Minimum Spanning Trees, and Dynamic Programming
Primary topics: greedy algorithms (scheduling, minimum spanning trees, clustering, Huffman codes) and dynamic programming (knapsack, sequence alignment, optimal search trees).
### Part 4: Shortest Paths Revisited, NP-Complete Problems and What To Do About Them
Primary topics: shortest paths (Bellman-Ford, Floyd-Warshall, Johnson), NP-completeness and what it means for the algorithm designer, and strategies for coping with computationally intractable problems (analysis of heuristics, local search).