Peter Jepson
@PeterAJepson
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Neural Network AI Snake. Full sigmoid. Arch[16,42,42,3]. Bellman Equation Approximation. C programming language. SDL2 gfx #ai #NeuralNetwork #sigmoid #sdl #c
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Each Neuron has a 'bias' which shifts its activation level, essentially switching it on or off. When a network is trained, the parameters of the network are slightly adjusted again and again, moving ever closer to representing training data.
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A fully connected Neural Network is made up of layers. Every Neuron in a layer is connected to every Neuron in the next layer. The first layer is input (x) and the last layer is output (y). Each connection has a 'weight' which represents the strength of the connection.
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The first implementation of an artificial Neuron was built by Frank Rosenblatt(1928 - 1972), with his Perceptron program.
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We may not yet know the full story of the brain, but we have known for quite some time the basic architecture of Neurons and when computer scientists first set out to build artificial intelligence, they attempted to model this architecture with artificial Neurons.
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Neurons consist of three parts; a Soma (cell body), Dendrites which receive signals and an Axon which sends signals. When a Neuron "fires", the Axon of that Neuron sends electrical and chemical signals to the Dendrites of another Neuron through a Synapse (gap).
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