How are nns related to statistical methods?

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Having multiple perceptrons can actually solve the XOR problem satisfactorily: this is because each perceptron can partition off a linear part of the space itself, and they can then combine their results. a) True – this works always, and these multiple perceptrons learn to classify even complex problems. b) False – perceptrons are mathematically incapable of solving linearly inseparable functions, no matter what you do c) True – perceptrons can do this but are unable to learn to do it – they have to be explicitly hand-coded d) False – just having a single perceptron is enough

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What is the difference between a Feedforward Neural Network and Recurrent Neural Network?

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what are some advantages and disadvantages of neural network?

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I need a MATLAB source code to recognize different regular geometric shapes such as: squares,rectangles,triangles,circles and ellipses in different sizes using neural network. All of the images containing these shapes should be in binary format with the size of 300*400 pixels. would you please give me a MATLAB code to detect these geometric shapes?

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Who is concerned with nns?

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Describe the structure of artificial neural networks?

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How many kinds of kohonen networks exist?

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 Which of the following is true? (i) On average, neural networks have higher computational rates than conventional computers. (ii) Neural networks learn by example. (iii) Neural networks mimic the way the human brain works. a) All of the mentioned are true b) (ii) and (iii) are true c) (i), (ii) and (iii) are true d) None of the mentioned

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 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

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How does an LSTM network work?

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What are the population, sample, training set, design set, validation set, and test set?

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