

Neural Networks Virtual Study Group - jcbozonier
http://groups.google.com/group/neural-networks-study-group

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almost
Seems like a great idea. Would be cool to see more of these...

Of course C# seems like a horrible choice for learning about this sort of
stuff, but maybe that's just me.

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signa11
hmm, i don't really think C# has anything to do with it, other than just
providing a vehicle for implementation of fundamental ideas of NN theory (imho
ofcourse).

in my opinion, using mathematica (or some such) would have been a far saner
choice, to get to the essence of the subject. also, a dosage of classical
(pioneering ?) work as described in (parallel-distributed-processing vol-1&2)
[http://www.amazon.com/Parallel-Distributed-Processing-Vol-
Fo...](http://www.amazon.com/Parallel-Distributed-Processing-Vol-
Foundations/dp/026268053X/ref=sr_1_1?ie=UTF8&s=books&qid=1232857316&sr=1-1),
would be just great.

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axiom
Oy! enough with the neural networks already.

Look, a neural network is not some magic machine that can solve all your
classification problems. A good 90% of applications of ANNs I've seen could
(read: should) have been replaced with a support vector machine, or a Bayesian
classifier, or some other proper statistically principled model.

I swear, I get the impression that people keep coming back to ANNs just
because the goddamn name sounds cool.

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jcbozonier
Some of us just don't know what they are or how to use them. I guarantee I'll
be forming another study group some time in the future on the other topics you
mentioned if they are as broad in application as you say. :)

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axiom
My advice would just be to take a few stats courses. Make sure you're
comfortable with your linear algebra inside out. Learn as many numerical
methods as possible etc. etc.

In my mind, neural networks should only be used when you're trying to model
actual biological systems. Otherwise, one should always use a proper model -
since it actually gives insight into what's going on with the system, instead
of just being a magic black box. Of course, notice that all commonly used ANN
topologies have nothing to do with biology - feed forward, hopfield nets,
kohonen maps etc. They have barely any resemblance to how actual neurons
behave. Basically, they are just heuristics with a cool sounding name.

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psyklic
It yells danger to me when only one week of course materials is not "under
construction."

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dustineichler
question: where else can i learn about neural networks and ai?

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signa11
my recommendations (for neural networks) would be as follows:

    
    
       - parallel distributed processing (PDP group vol 1 & 2)
       - simon haykin (Neural Networks and Learning Machines)
       - christopher bishop (Neural Networks for Pattern Recognition)

