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Back propagation is a learning technique that adjusts weights in the neutral network by propagating weight changes.

  1. Forward from source to sink
  2. Backward from sink to source
  3. Forward from source to hidden nodes
  4. Backward from sink to hidden nodes
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2 Answers

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Ans B

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Why it can't be option D as back propogation is multilayer feedbackward so it has hidden layers too. .
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We ultimately have to back-propogate the error to the input layer.....
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Back propagation is a learning technique that adjusts weights in the neural network by propagating weight changes backward from sink to source.

So, the correct option is:

Backward from sink to source

Answer:

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