What does the term 'backpropagation' refer to in neural networks?

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Question: What does the term \'backpropagation\' refer to in neural networks?

Options:

Correct Answer: The method of updating weights based on error

Solution:

Backpropagation is the algorithm used to update the weights of the network by calculating the gradient of the loss function.

What does the term 'backpropagation' refer to in neural networks?

What does the term 'backpropagation' refer to in neural networks?

Step 1: Understand that a neural network is made up of layers of nodes (neurons) that process information.
Step 2: When the network makes a prediction, it calculates an output based on its current weights.
Step 3: The prediction is compared to the actual result to find out how wrong it was. This difference is called the 'loss'.
Step 4: Backpropagation is the process of sending this loss information back through the network.
Step 5: As the loss is sent back, the algorithm calculates how much each weight contributed to the error.
Step 6: Using this information, the algorithm updates the weights to reduce the loss in future predictions.

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