Lets build a program that will teach the computer to recognize simple patterns using neural networks. Artificial neural networks, like real brains, are formed from connected "neurons", all capable of carrying out a data-related task, such as answering a question about the relationship between them. Let's take the following pattern: 1 1 1 = 1 1 0 1 = 1 0 1 1 = 0 Each input, and the output can be only a 1 or a 0. If we look closer, we will realize that the output is 1, if the first input is 1. However, we will not tell that to the computer. We will only provide the sample inputs and outputs and ask it to "guess" the output of the input 1 0 0 (which should be 1). To make it really simple, we will just model a single neuron, with three inputs and one output. The three examples above are called a training set. We're going to train the neuron to work out the pattern and solve the task for input 1 0 0, by just having the training set and without know...
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