

The Netflix Prize and Production Machine Learning Systems: An Insider Look - nkurz
http://blogs.mathworks.com/loren/2015/04/22/the-netflix-prize-and-production-machine-learning-systems-an-insider-look/

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compbio
I think the author is too constrained to promote Matlab, so the better
(production-ready) alternatives are left out.

Furthermore, I do not understand why this is called an "insider look", when it
is about someone reading a blog from 2012 and basically giving a recap.

Finally, I think it is time to move past this trope of "Netflix wasted 1
million dollars on a solution they did not even use". Probably the entire top
20 of the Netflix competition had a good enough score to build upon -- no need
to focus only on the solution from the (rather lucky) winners. We are six
years after this competition and the community is still talking about it. Now
how is that for marketing?

There is no mention of Factorization Machines (
[http://www.libfm.org/](http://www.libfm.org/) ). A technique spawned with
this competition which revolutionized recommendation engines and is definitely
in use at Netflix now. Instead they keep harping on 'Collaborative Filtering'
when that is a very basic technique (obviously supported by Matlab).

I miss a mention of power tools (Vowpal Wabbit has fast production-ready
scalable matrix factorization which can fit on a 1 million dataset on a
laptop:
[https://github.com/JohnLangford/vowpal_wabbit/tree/master/de...](https://github.com/JohnLangford/vowpal_wabbit/tree/master/demo/movielens)
) and of customers actually running Matlab based recommendation engines on
scale.

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nl
If this is interesting then I recommend (ha!) the EdX Spark course[1]. One
assignment shows how to build a recommender on the MovieLens dataset mentioned
in this article.

[1] [https://www.edx.org/course/introduction-big-data-apache-
spar...](https://www.edx.org/course/introduction-big-data-apache-spark-uc-
berkeleyx-cs100-1x)

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amelius
Is Google taking advantage of these techniques as well? (What one person
clicked might be interesting for others with a similar clicking behavior as
well).

