[Article.Ai] A giant intuitive diagram showing how an artificial neural network permits backward propagation of error signals
Giant intuitive diagram showing how an artificial neural network works; by allowing error signals (aka changes in costs) to “trickle” backwards from the output layer.
For example: “Trickling” backwards simply means a value (aka cost) computed at some neuron j in layer L is input to values generated by computations of some prior neuron k in layer L-1. Some cost computed from neuron k then becomes input to values generated by computations of some prior neuron m, in layer L-2.
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Amazon:
https://www.amazon.com/dp/B077FX57ZZ
Free copy with equations that are nicely coloured differently than their surrounding text content (instead of equations with the same colouring as their surrounding text content)…on research gate :
https://www.researchgate.net/publication/321162382_Artificial_Neural_Nets_For_Kids
Free copy on quora:
https://www.quora.com/What-is-the-most-intuitive-explanation-of-artificial-neural-networks/answer/Jordan-Bennett-9
Nice youtube video:
https://www.youtube.com/watch?v=aP66xxe8z1g
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Author:
I am a casual body builder, and software engineer.
