

Azure – Machine Learning as a Service - BIackSwan
http://azure.microsoft.com/en-us/campaigns/machine-learning/

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orf
The video is full of stock footage of business people doing businessy things
but light on actual information, which is a shame because the service looks
very interesting.

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cmelbye
Seriously. If this is such a great product, couldn't they have shown a
screencast demonstrating what the narrator was saying instead of showing
tangentially related stock video?

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waterside81
Our company mulled the idea of doing a similar product for years. Essentially
putting a pretty UI on top of machine learning algorithms under the hood where
you automatically determine which algo gives the best fit.

Ultimately shelved it because we couldn't find a good customer fit. For
corporate enterprise users, our usual bread & butter, this has to be super
secure so the idea of uploading gigs of proprietary company data or customer
data rings alarm bells. Plus the data has to be cleaned up and ready to go. It
just seemed like a lot of leg work before you even got to the payoff - and
even then, having to explain why the predictive results weren't 100% accurate
etc.

Curious to see how this plays out. I wonder if they're using vowpal-wabbit
under the hood - I believe the guy behind that worked / works at MSFT.

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agibsonccc
I'm on the opposite end of the market, but I'd be curious to see who would use
ML as a service. I've never seen the use case for it being in the ML space
myself. Anyone care to step up and state their use case?

How much data do you typically throw at these APIs? How effective have they
been for you overall? Did you need a super accurate model?

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sytelus
Like most other exponential growth patterns, there is suddenly HUGE number of
people now wanting to use ML but don't have necessary background. Pretty much
every other enterprisy developer who had been happily spending their lives
pushing data from RDBMS to/from UI now wants to try out ML for something or
other. Unfortunately current state of ML framework is a minefield. If you
don't know your precision from recall or confusion table really confuses you
or have no clue when you have been merely overfitting all along, you are
screwed.

I can see huge market if you can bottle down complexities of ML in a nice easy
to use package. A very easy to use ML service or tool would allows you to
import your data with few clicks, apply normalization such as stemming or edit
distance by pick-n-choose without writing any code, has nice generic
featurization library, can run tons of algorithms with large number of
parameter sweeps, does automatic feature selection, takes care of maintaining
test and validation sets etc. This kind of thingy would be super popular. My
guess is that it has to run in cloud because it eliminates all the setup and
updates plus doing what I described even on moderate size data sets usually
takes hours on single machine. Now throw in plug-n-pray deep learning algos
which even few ML experts are familiar with and can require significant GPU
based infrastructure.

Can this be reality? In my opinion, this is more in line of those graphical
tools that claims you can create programs without having to learn programming.
It's impressive when you do demo but don't last long in battle grounds.
Ultimately, if you want to write program, you will need to get your hands and
cloths dirty with oil stinks. If you want to do machine learning, you will
need to start from stats and probability.

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agibsonccc
When I said I'm on the other side, I met I'm one of those crazy machine
learning guys[1] who doesn't see a business model in the full blown package.

You're right that this would be hard, but I'm wondering if the cost benefit
analysis is there for it. I looked at this approach, and I don't believe it is
relative to the costs incurred for something like this. I'd be willing to give
it a shot at some point maybe, but neural nets behind the scenes for me
involves more fun data behind fire walls ;).

[1] [http://wired.com/2014/06/skymind-deep-
learning/](http://wired.com/2014/06/skymind-deep-learning/)

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sandstrom
Anyone know how this is different from, say, prediction.io?

[http://prediction.io/](http://prediction.io/)

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louisdorard
Prediction.io needs a server to run on, and it focuses on recommendation
problems, so it doesn't seem to do classification and regression for instance.

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gregrata
Looks really interesting. Anyone find any links with actual info, as this page
is pure fluff!?

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saosebastiao
This has the potential to be huge, if they decide to tap into the vast
knowledge-base that Microsoft Research has developed over the years. I would
jump at the chance to use an original implementation of their research on
Decision Forests.

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dev360
Wow - Google Prediction like API with CIO approved corporate drones? Check!
Only took them 4 years to catch up.

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taliesinb
The "ML Studio" that briefly appears in the video looks like a slicker version
of Weka.

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igravious
Missed a trick to call it Mlaases.

