Assertion: neural network's neuron | /r/HasAspect | bias
Facets:
value: w =  - b
type: OTHER
Source sentences:
text: Shared weights and biases: I've said that each hidden neuron has a bias and $5 \times 5$ weights connected to its local receptive field.
text: Each neuron has the same weights and bias: - w =  - b = 0 ''' def __init__ ( self ) : weights = np . array ( [ 0 , 1 ] ) bias = 0 self .
text: Just like in real life, the lazy ones that play it safe (low and infrequent activations) skate by blame free while the neurons that do the most work get blamed and have their weights and biases modified.
text: Convolutional neural networks are similar to feed forward neural networks, where the neurons have learnable weights and biases.
text: Convolutional Neural Networks are very similar to ordinary Neural Networks, they are made up of neurons that have learnable weights and biases.
text: Convolutional Neural Networks are very similar to ordinary Neural Networks from the previous chapter: they are made up of neurons that have learnable weights and biases.