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Mining of Massive Datasets

109 pointsby markhkimover 8 years ago

5 comments

joaoricoover 8 years ago
This coursera course was taken down, but it is now up and running at lagunita.stanford.edu [0], which uses edx&#x27;s open source platform [1]. The same happened to other stanford courses previously on coursera, you can find them here [2], including Compilers, Automata Theory, and Convex Optimization.<p>[0] <a href="https:&#x2F;&#x2F;lagunita.stanford.edu&#x2F;courses&#x2F;course-v1:ComputerScience+MMDS+Fall2016&#x2F;about" rel="nofollow">https:&#x2F;&#x2F;lagunita.stanford.edu&#x2F;courses&#x2F;course-v1:ComputerScie...</a><p>[1] <a href="https:&#x2F;&#x2F;open.edx.org&#x2F;" rel="nofollow">https:&#x2F;&#x2F;open.edx.org&#x2F;</a> <a href="https:&#x2F;&#x2F;github.com&#x2F;edx&#x2F;edx-platform" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;edx&#x2F;edx-platform</a><p>[2] <a href="https:&#x2F;&#x2F;lagunita.stanford.edu&#x2F;courses" rel="nofollow">https:&#x2F;&#x2F;lagunita.stanford.edu&#x2F;courses</a>
PaulHouleover 8 years ago
What amazed me is how much of this is 1990s stuff.
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mrcactu5over 8 years ago
massive is an understatement. I have only dealt with puny GB sized data sets. They deal with vectors which cannot fit into main memory.
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leksakover 8 years ago
Deadlines are at the 29th of November. Best of luck
nthcolumnover 8 years ago
tldr; parallel map reduce. ;)