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Artificial Neural Networks-Biological Neural Network-Comparison-Artificial Vs Biological Neuron

[@vedikanemane7781]

Best and such a precise explanation!👍👍

[@preethij427]

Thank you

[@amanvishwakarma2064]

Good job

[@preethij427]

Thanks

[@pkr1kajdjasdljskjdjsadjlaskdja]

nice

[@preethij427]

Thanks

[@johnsvilla3279]

notes please

[@ravimalhotra7780]

notes pdf please

[@navneetkashyap7748]

What is weight?

[@preethij427]

In an artificial neural network, the term "weight" refers to the strength of the connection between two neurons. Each connection between neurons has an associated weight that influences the information flow between them. These weights are the parameters that the neural network learns during the training process. The weights determine the impact of one neuron on another. During the training phase, the network adjusts these weights to minimize the difference between the predicted output and the actual output, allowing the network to learn patterns and relationships within the input data. In summary, weights in a neural network play a crucial role in determining the significance of inputs and shaping the network's behavior.