An auto-associative network is:
a) a neural network that contains no loops
b) a neural network that contains feedback
c) a neural network that has only one loop
d) a single layer feed-forward neural network with pre-processing
Which is the similar operation performed by the drop-out in neural network?
What are the applications of a Recurrent Neural Network (RNN)?
How are weights initialized in a network?
How does ill-conditioning affect nn training?
How artificial neural networks can be applied in future?
What is Pooling in CNN and how does it work?
Which of the following is not the promise of artificial neural network? a) It can explain result b) It can survive the failure of some nodes c) It has inherent parallelism d) It can handle noise
How are artificial neural networks different from normal computers?
How does an LSTM network work?
A 4-input neuron has weights 1, 2, 3 and 4. The transfer function is linear with the constant of proportionality being equal to 2. The inputs are 4, 10, 5 and 20 respectively. The output will be: a) 238 b) 76 c) 119 d) 123
What are cases and variables?
How to avoid overflow in the logistic function?