How does a neural network learn?
An example of an AI chatbot conversation about how neural networks learn from data.
Can you explain how a neural network learns from data?
Sure! A neural network learns by adjusting its weights based on the data it processes, using a method called backpropagation.
What is backpropagation?
Backpropagation is an algorithm that calculates the gradient of the loss function and updates the weights to minimize errors.
How does the network know what weights to adjust?
The network uses a loss function to measure the difference between predicted and actual outputs, guiding the weight adjustments.
Can you give an example of a loss function?
A common loss function is Mean Squared Error, which calculates the average squared difference between predicted and actual values.
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