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        "author": "SiCNN Author",
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        "description": "# Simple Neural Net Module\n\nInstall requirement:\n\n<code>pip install numpy</code>\n\nInstall module:\n\n<code>pip install SiNN</code> or download <code>module.py</code> from GitHub.\n\n# Quick-Start Guide\nImport SiNN: <code>import SiNN</code>\n\nInitialize the neural net:\n<code>neuralnet = SiNN.NeuralNetwork(3) # 3 is the number of inputs</code>\n\nCreate a variable with training set inputs:\n\n<code>ins = array([[1a, 1b, 1c], [2a, 2b, 2c], [3a, 3b, 3c]])</code>\n\nSet the expected outcomes (training set outs):\n\n<code>outs = array([[1,1,0]]).T # don't worry about the .T</code>\n\nTrain with <code>neuralnet.train(ins, outs, iters)</code>, where iters is the amount of training cycles. A number around 1000 is normally good for simple uses.\n\nThen, see if it works with <code>neuralnet.think([a,b,c])</code>.\n\nPresent it with a new situation with neuralnet.think(newsit)\n\nNote: use python 3 with this.\n\n\n",
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        "summary": "A simple way to make neural nets: Machine learning without linear algebra",
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