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Artificial neural networks (ANNs) are a broad class of computational models loosely based on biological neural networks. They encompass feedforward NNs (including "deep" NNs), convolutional NNs, recurrent NNs, etc.

4 votes

Struggling to make a neural network mimic a basic if statement

The curvature of the cost surface with these particular inputs and outputs makes this a bit of a pathological example. A 'good' solution can be found by just outputting 0.333 all the time, and if you …
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3 votes
Accepted

Stochastic gradient descent for neural networks with tied weights

First of all, shouldn't your equation (1) be the following? $$ \frac{\partial E}{\partial w_{tied}} = \frac{\partial E}{\partial f}(\frac{\partial f}{\partial h_1}\frac{\partial h_1}{\partial w_1}+\fr …
nlml's user avatar
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2 votes

Image classification, narrow domain with custom labels

Here's one tutorial on training a deep convnet from scratch in Keras. There should be plenty of other examples on the web. You could still use a pre-trained model for this, and just re-train some of …
nlml's user avatar
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