Assertion: neural network's weight | /r/HasProperty | initialized high values
Facets:
value: very
type: DEGREE
value: the term np.dot(w,x)+b becomes
type: OTHER
Source sentences:
text: is that what happens if weights are initialized high values or very low values and what is a reasonable initialization of weight values.
text: If weights are initialized with very high values the term np.dot(W,X)+b becomes significantly higher and if an activation function like sigmoid() is applied, the function maps its value near to 1 where the slope of gradient changes slowly and learning takes a lot of time.