Understanding Neural Nets

David Smith links to a video which explains how neural networks do their thing:

In R, you can train a simple neural network with just a single hidden layer with the nnet package, which comes pre-installed with every R distribution. It’s a great place to start if you’re new to neural networks, but the deep learning applications call for more complex neural networks. R has several packages to check out here, including MXNetdarchdeepnet, and h2o: see this post for a comparison. The tensorflow package can also be used to implement various kinds of neural networks.

R makes it pretty easy to run one, though it then becomes important to understand regularization as a part of model tuning.

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Logistic Regression In R

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Feature Improvements In Microsoft R Server 9.1

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