What are combination, activation, error, and objective functions?

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The network that involves backward links from output to the input and hidden layers is called as ____. a) Self organizing maps b) Perceptrons c) Recurrent neural network d) Multi layered perceptron

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How artificial neurons learns?

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Why is the XOR problem exceptionally interesting to neural network researchers? a) Because it can be expressed in a way that allows you to use a neural network b) Because it is complex binary operation that cannot be solved using neural networks c) Because it can be solved by a single layer perceptron d) Because it is the simplest linearly inseparable problem that exists.

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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

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What are the different layers in CNN?

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Which is the similar operation performed by the drop-out in neural network?

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What are batch, incremental, on-line, off-line, deterministic, stochastic, adaptive, instantaneous, pattern, constructive, and sequential learning?

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Why use artificial neural networks? What are its advantages?

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What are the applications of a Recurrent Neural Network (RNN)?

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How artificial neural networks can be applied in future?

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What is artificial intelligence neural networks?

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