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What is the role of backpropagation in training neural networks?
Practice Questions
Q1
What is the role of backpropagation in training neural networks?
To initialize weights
To update weights based on error
To normalize input data
To select features
Questions & Step-by-Step Solutions
What is the role of backpropagation in training neural networks?
Steps
Concepts
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.
No concepts available.
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