
Mining of Massive Datasets - markhkim
http://www.mmds.org/
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joaorico
This coursera course was taken down, but it is now up and running at
lagunita.stanford.edu [0], which uses edx'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.

[0]
[https://lagunita.stanford.edu/courses/course-v1:ComputerScie...](https://lagunita.stanford.edu/courses/course-v1:ComputerScience+MMDS+Fall2016/about)

[1] [https://open.edx.org/](https://open.edx.org/)
[https://github.com/edx/edx-platform](https://github.com/edx/edx-platform)

[2]
[https://lagunita.stanford.edu/courses](https://lagunita.stanford.edu/courses)

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PaulHoule
What amazed me is how much of this is 1990s stuff.

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cantagi
How do you mean? Do you know of any up-to-date books on large scale data
mining?

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mrcactu5
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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infinitone
Yes, in general what they refer to are things like the IRS Tax records (250
TB), Yahoo Ad data (900 TB). You just can't use a single machine to work with
such data.

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leksak
Deadlines are at the 29th of November. Best of luck

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nthcolumn
tldr; parallel map reduce. ;)

