How neural networks became a universal function approximators?
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What is the role of activation functions in a Neural Network?
What is simple artificial neuron?
What is the advantage of pooling layer in convolutional neural networks?
What are conjugate gradients, levenberg-marquardt, etc.?
What is back propagation? a) It is another name given to the curvy function in the perceptron b) It is the transmission of error back through the network to adjust the inputs c) It is the transmission of error back through the network to allow weights to be adjusted so that the network can learn. d) None of the mentioned
How are layers counted?
Neuro software is: a) A software used to analyze neurons b) It is powerful and easy neural network c) Designed to aid experts in real world d) It is software used by Neuro surgeon
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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
Which is true for neural networks? a) It has set of nodes and connections b) Each node computes it’s weighted input c) Node could be in excited state or non-excited state d) All of the mentioned
Explain neural networks?
What are the population, sample, training set, design set, validation set, and test set?
How artificial neurons learns?
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