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How neural networks became a universal function approximators?
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Describe the structure of artificial neural networks?
How neural networks became a universal function approximators?
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 the population, sample, training set, design set, validation set, and test set?
What can you do with an nn and what not?
Who is concerned with nns?
What are neural networks and how do they relate to ai?
List some commercial practical applications of artificial neural networks?
Neural Networks are complex ______________ with many parameters. a) Linear Functions b) Nonlinear Functions c) Discrete Functions d) Exponential Functions
Which of the following is an application of NN (Neural Network)? a) Sales forecasting b) Data validation c) Risk management d) All of the mentioned
What is Pooling in CNN and how does it work?
How are weights initialized in a network?
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