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Neural Networks Demystified

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Re: Neural Networks Demystified

#6
It's a great short introduction, really worth looking through the code examples that they have on github too - https://github.com/stephencwelch/Neural-Networks-Demystified

There is certainly no shortage of new tutorials bubbling up on neural nets. One of my favorites - https://www.cs.ox.ac.uk/people/nando.defreitas/machinelearni...

Re: Neural Networks Demystified

#7
post #3

no one can ever claim there that is a shortage of tutorials with regard to neural nets (and deep learning)

Tutorials - sure. Actual rigorous analysis - not at all.

Well, this is pretty good http://neuralnetworksanddeeplearning.com/

Also these lecture notes https://github.com/joanbruna/stat212b

Re: Neural Networks Demystified

#9
post #7
post #3

Earlier quoted context omitted.

Tutorials - sure. Actual rigorous analysis - not at all.

Well, this is pretty good http://neuralnetworksanddeeplearning.com/ Also these lecture notes https://github.com/joanbruna/stat212b

No no, I mean the theoretical analysis of neural networks. It's true that some authors attempt to do that, in fact even famous researches attempt to do this. However their arguments and analysis often breakdown in the general case and what their papers boil down to is that neural networks are good at modeling functions that they are good at modeling.

In fact the state of the field of machine learning is essentially the state of mathematics before Cauchy and Weierstrass.

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