What are the applications of a Recurrent Neural Network (RNN)?
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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
Why use artificial neural networks? What are its advantages?
What are the population, sample, training set, design set, validation set, and test set?
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
What are the disadvantages of artificial neural networks?
What are cases and variables?
How are nns related to statistical methods?
How artificial neural networks can be applied in future?
Why is the XOR problem exceptionally interesting to neural network researchers? a) Because it can be expressed in a way that allows you to use a neural network b) Because it is complex binary operation that cannot be solved using neural networks c) Because it can be solved by a single layer perceptron d) Because it is the simplest linearly inseparable problem that exists.
What are artificial neural networks?
What learning rate should be used for backprop?
Explain Generative Adversarial Network.
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