A perceptron adds up all the weighted inputs it receives, and if it exceeds a certain value, it outputs a 1, otherwise it just outputs a 0.
a) True
b) False
c) Sometimes – it can also output intermediate values as well
d) Can’t say
Why use artificial neural networks? What are its advantages?
How to avoid overflow in the logistic function?
How many kinds of nns exist?
What are the applications of a Recurrent Neural Network (RNN)?
What are the population, sample, training set, design set, validation set, and test set?
How neural networks became a universal function approximators?
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
What are conjugate gradients, levenberg-marquardt, etc.?
What are cases and variables?
How does an LSTM network work?
Which of the following is true for neural networks? (i) The training time depends on the size of the network. (ii) Neural networks can be simulated on a conventional computer. (iii) Artificial neurons are identical in operation to biological ones. a) All of the mentioned b) (ii) is true c) (i) and (ii) are true d) None of the mentioned
What are artificial neural networks?
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