What is the role of backpropagation in training neural networks?

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Question: What is the role of backpropagation in training neural networks?

Options:

Correct Answer: To update weights based on error

Solution:

Backpropagation is an algorithm used to update the weights of the neural network based on the error calculated from the output.

What is the role of backpropagation in training neural networks?

What is the role of backpropagation in training neural networks?

Step 1: A neural network makes a prediction based on input data.
Step 2: The prediction is compared to the actual result to calculate the error (how wrong the prediction was).
Step 3: Backpropagation starts by taking this error and calculating how much each weight in the network contributed to that error.
Step 4: The algorithm then adjusts the weights to reduce the error, making the network's predictions more accurate in the future.
Step 5: This process is repeated many times with different data to improve the network's performance.

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