What are artificial neural networks?
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Who is concerned with nns?
What are combination, activation, error, and objective functions?
How are nns related to statistical methods?
How artificial neurons learns?
What learning rate should be used for backprop?
Explain Generative Adversarial Network.
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
The name for the function in question 16 is a) Step function b) Heaviside function c) Logistic function d) Perceptron function
What can you do with an nn and what not?
What are cases and variables?
Why use artificial neural networks? What are its advantages?
What are artificial neural networks?
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