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In a neural network, what does the term 'backpropagation' refer to?
In a neural network, what does the term 'backpropagation' refer to?
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In a neural network, what does the term 'backpropagation' refer to?
The process of forward propagation of inputs
The method of updating weights based on error
The initialization of network parameters
The evaluation of model performance
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Backpropagation is the algorithm used to update the weights of the network by calculating the gradient of the loss function.
Questions & Step-by-step Solutions
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Q: In a neural network, what does the term 'backpropagation' refer to?
Solution:
Backpropagation is the algorithm used to update the weights of the network by calculating the gradient of the loss function.
Steps: 6
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Step 1: Understand that a neural network learns by adjusting its weights.
Step 2: When the network makes a prediction, it calculates an error (loss) based on how far off the prediction is from the actual result.
Step 3: Backpropagation is the process of sending this error back through the network.
Step 4: During backpropagation, the algorithm calculates how much each weight contributed to the error.
Step 5: The algorithm then updates the weights to reduce the error in future predictions.
Step 6: This process is repeated many times with different data to improve the network's accuracy.
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