1
$\begingroup$

My question is very simple: which learning resources (books, courses, online courses, and so on) about "large data analysis" would you suggest to a graduate with a strong background in Machine Learning and Computer Science?

Edit: I am looking for something similar to section 17 of this very well known online course: https://www.coursera.org/course/ml (you can click on preview lectures to check it out) but in very much detail and many other different methods/algorithms.

$\endgroup$
1
$\begingroup$

New York University has a course on Large Scale data analysis that covers most of the topics (and many more) I was looking for. It is very complete and all the materials are available (videos and slides):

http://cilvr.cs.nyu.edu/doku.php?id=courses:bigdata:slides:start

Additionally, further information about Stochastic Methods is available in this presentation:

http://research.microsoft.com/en-us/um/cambridge/events/mls2013/downloads/stochastic_gradient.pdf

$\endgroup$
0
$\begingroup$

The Udacity course Introduction to Hadoop and MapReduce might be a good place to start.

Addition in response to question edit: Maybe the textbook Mining of Massive Datasets would be useful.

$\endgroup$
  • $\begingroup$ Thank you for your suggestion. I already knew about that course, but it is too specific in my opinion. I am looking for something that extends section 17 of this very well known online course: coursera.org/course/ml (you can click on preview lectures to check it out). $\endgroup$ – Pablo Suau Dec 11 '13 at 8:53
0
$\begingroup$

I'm a fan of these YouTube videos by Nando de Freitas:

http://www.youtube.com/user/ProfNandoDF/videos

$\endgroup$
  • $\begingroup$ Thank you for the suggestion. However, I didn't see any video about the specific topic of large data analysis. $\endgroup$ – Pablo Suau Dec 13 '13 at 9:19

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Not the answer you're looking for? Browse other questions tagged or ask your own question.