Multilayer Perceptron (MLP)
Multilayer Perceptron (MLP) ni mtandao wa kawaida wa neva unaounganishwa kikamilifu unaofunzwa kwa kutumia algoriti ya backpropagation, kama ilivyofafanuliwa na Rumelhart, Hinton & Williams katika karatasi yao muhimu ya 1986 katika Nature. Kwa kuwa na safu ya pembejeo, safu moja au zaidi za seli za neva za siri, na safu ya matokeo, MLP hujifunza miundo isiyo ya mstari kutoka kwa vipengele vya pembejeo hadi matokeo yanayolengwa na hutumika kama msingi mkuu wa akili bandia ya kisasa.
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Vyanzo
- Rumelhart, D. E., Hinton, G. E. & Williams, R. J. (1986). Learning representations by back-propagating errors. Nature, 323, 533–536. DOI: 10.1038/323533a0 ↗
- Goodfellow, I., Bengio, Y. & Courville, A. (2016). Deep Learning (Ch. 6–8). MIT Press. ISBN: 978-0-262-03561-3
- Bishop, C. M. (2006). Pattern Recognition and Machine Learning (Ch. 5). Springer. ISBN: 978-0-387-31073-2
Jinsi ya kunukuu ukurasa huu
ScholarGate. (2026, June 3). Multilayer Perceptron (Fully Connected Feedforward Neural Network). ScholarGate. https://scholargate.app/sw/deep-learning/multilayer-perceptron
Which method?
Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.
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