How many kinds of kohonen networks exist?
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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
What is the role of activation functions in a Neural Network?
What learning rate should be used for backprop?
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
What is a neural network and what are some advantages and disadvantages of such a network?
What is simple artificial neuron?
How are weights initialized in a network?
What are combination, activation, error, and objective functions?
What are the population, sample, training set, design set, validation set, and test set?
Describe the structure of artificial neural networks?
Explain neural networks?
How does an LSTM network work?
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