Algorithms: Design and Analysis - Part 2 [Coursera / Stanford University]

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Added on December 14, 2014 by diypromoin Other > Tutorials
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Algorithms: Design and Analysis - Part 2 [Coursera / Stanford University] (Size: 1.52 GB)
 2 - 6 - Graph Search - Overview [Part I Review - Optional] (23 min).srt40.17 KB
 2 - 7 - Dijkstras Shortest-Path Algorithm [Part I Review - Optional] (21 min).srt33.72 KB
 2 - 1 - About the Course [Part I Review - Optional] (17 min).srt31.36 KB
 2 - 9 - Heaps Operations and Applications [Part I Review - Optional] (18).srt29.94 KB
 2 - 2 - Why Study Algorithms [Part I Review - Optional] (19 min).srt29.2 KB
 8 - 3 - A Greedy Algorithm (17 min).srt26.41 KB
 2 - 3 - Guiding Principles for Analysis of Algorithms [Part I Review - Optional] (15 min).srt25.3 KB
 19 - 6 - Random Walks on a Line (16 min).srt24.24 KB
 2 - 5 - Graph Representations [Part I Review - Optional] (14 min).srt23.69 KB
 5 - 3 - Correctness Proof I (16 min).srt23.57 KB
 9 - 3 - A Greedy Algorithm (17 min) [16506eac].mp424.7 MB
 2 - 6 - Graph Search - Overview (23 min) [e49996be].mp424.36 MB
 8 - 7 - The Ackermann Function (16 min) [82173278].mp422.64 MB
 20 - 1 - Stable Matching (15 min) [d1eea025].mp422.55 MB
 8 - 3 - Analysis of Union-by-Rank (15 min) [40e822a2].mp422.29 MB
 2 - 7 - Dijkstras Shortest-Path Algorithm (21 min) [cbc12e6c].mp421.92 MB
 19 - 7 - Analysis of Papadimitriou's Algorithm (15 min) [0723a39a].mp421.8 MB
 8 - 4 - Path Compression (15 min) [f168bafc].mp421.51 MB
 19 - 6 - Random Walks on a Line (16 min) [ca621623].mp421.33 MB
 17 - 4 - The Traveling Salesman Problem (15 min) [d5b10502].mp421 MB

Description

Publisher: Coursera / Stanford University
Author: Tim Roughgarden
Duration: 19:04:49

Video: H263 (MP4), 960:540, 30fps
Audio: mp4a, 44100 Hz, stereo

Get Algorithms: Design and Analysis - Part 1 Here

Description:

In this course you will learn several fundamental principles of advanced algorithm design. You'll learn the greedy algorithm design paradigm, with applications to computing good network backbones (i.e., spanning trees) and good codes for data compression. You'll learn the tricky yet widely applicable dynamic programming algorithm design paradigm, with applications to routing in the Internet and sequencing genome fragments. You’ll learn what NP-completeness and the famous “P vs. NP” problem mean for the algorithm designer. Finally, we’ll study several strategies for dealing with hard (i.e., NP-complete problems), including the design and analysis of heuristics. Learn how shortest-path algorithms from the 1950s (i.e., pre-ARPANET!) govern the way that your Internet traffic gets routed today; why efficient algorithms are fundamental to modern genomics; and how to make a million bucks in prize money by “just” solving a math problem!


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1.52 GB
seeders:36
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Algorithms: Design and Analysis - Part 2 [Coursera / Stanford University]

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TechieAce
Thanks Buddy !
viru338
Thanks mate :)