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Tuesday, March 31, 2020

MIT OpenCourseWare, Algorithm, MIT, OCW, 1 of 47






MIT OpenCourseWare


1. Algorithmic Thinking, Peak Finding


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Labels: Algorithm, MIT, MIT OpenCourseWare, OCW
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ALGORITHM
A01. GeeksLesson
| playlists


A02. Tim Roughgarden
| Computer Scientist | Stanford University


01. Algorithms Full Course || Design and Analysis of Algorithms | 11:59:23 | Tim Roughgarden | Stanford University | Computer Scientist | Geek's Lesson
In mathematics and computer science, an algorithm is a finite sequence of well-defined, computer-implementable instructions, typically to solve a class of problems or to perform a computation.

In this course you will learn about the design and analysis of #algorithms​.

⭐️ Table of Contents ⭐️
0:00:03​ Why study algorithms
0:04:18​ Integer multiplication
0:12:56​ Karatsuba multiplication
0:25:35​ Merge sort
0:34:20​ Merge sort pseudocode
0:47​​​:11 Merge sort analysis
0:56:13​ Principles for analysis of algorithms
1:11:29​ Big oh notation
1:15:38​ Basic examples
1:19:53​ Big omega and theta
1:27:24​ Additional examples
1:35:15​ Log n algorithm
1:40:41​ Subcubic matrix multiplication algorithm
3:35:52​ Quicksort overview
4:04:44​ Partitioning around a pivot
4:23:29​ Choosing a good pivot
4:33:29​ A decomposition principle
4:55:17​ Algorithm analysis: key insights
5:16:01​ Randomized selection
5:50:18​ Deterministic selection
6:29:16​ Omega log n lower bound for comparison
6:42:46​ Graphs and minimum cuts
6:58:37​ Graphs representation
7:12:59​ Random contraction algorithm
7:21:44​ Analysis of contraction algorithm
7:51:48​ Counting minimum cuts
7:59:06​ Graph search overview
8:22​​​:26 Breadth first search
8:57:41​ Depth first search
9:05:05​ Topological sort
9:45:48​ Dijkstra's algorithm
10:22:39​ Data Structures
10:27:15​ Heaps operations
10:45:27​ Balanced search tree
10:56:22​ Binary search tree

⭐️ Credit ⭐️
Course Provided by: Stanford Algorithms
Course Author: Professor Tim Roughgarden
This course is provided here only for educational purpose.

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