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What does the term 'learning rate' control in a neural network?
What does the term 'learning rate' control in a neural network?
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What does the term 'learning rate' control in a neural network?
The number of layers in the network
The speed of weight updates
The size of the training dataset
The complexity of the model
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The learning rate determines how much to change the model in response to the estimated error each time the model weights are updated.
Questions & Step-by-step Solutions
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Q: What does the term 'learning rate' control in a neural network?
Solution:
The learning rate determines how much to change the model in response to the estimated error each time the model weights are updated.
Steps: 4
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Step 1: Understand that a neural network learns by adjusting its weights based on errors it makes.
Step 2: The learning rate is a number that tells the network how big of a change to make to the weights when it learns from an error.
Step 3: A small learning rate means the network makes tiny adjustments, while a large learning rate means it makes big adjustments.
Step 4: If the learning rate is too high, the network might overshoot the best solution. If it's too low, learning can be very slow.
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