How artificial neural networks can be applied in future?
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How are nns related to statistical methods?
What are the population, sample, training set, design set, validation set, and test set?
Which of the following is true? Single layer associative neural networks do not have the ability to: (i) perform pattern recognition (ii) find the parity of a picture (iii)determine whether two or more shapes in a picture are connected or not a) (ii) and (iii) are true b) (ii) is true c) All of the mentioned d) None of the mentioned
What are neural networks? What are the types of neural networks?
What are the disadvantages of artificial neural networks?
What are conjugate gradients, levenberg-marquardt, etc.?
How many kinds of kohonen networks exist?
A 3-input neuron is trained to output a zero when the input is 110 and a one when the input is 111. After generalization, the output will be zero when and only when the input is: a) 000 or 110 or 011 or 101 b) 010 or 100 or 110 or 101 c) 000 or 010 or 110 or 100 d) 100 or 111 or 101 or 001
What are artificial neural networks?
How to avoid overflow in the logistic function?
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 can you do with an nn and what not?
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