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Building Neural Networks

Building a neural network for particular problems requires multiple steps:
1. Determine the input and outputs of the problem;
2. Start from the simplest imaginable network, e.g. a single feed-forward perceptron;
3. Find the connection weights to produce the required output from the given training data input;
4. Ensure that the training data passes successfully, and test the network with other training/testing data;
5. Go back to Step 3 if performance is not good enough;
6. Repeat from Step 2 if Step 5 still lacks performance; or
7. Repeat from Step 1 if the network in Step 6 does still not perform well enough.

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