What are weights in a neural network?
An example of an AI chatbot conversation about weights in neural networks.
What are weights in a neural network?
Weights in a neural network are parameters that transform input data within the network. They determine the strength of the connection between neurons.
How do weights affect the learning process?
Weights are adjusted during training to minimize the error in predictions. This adjustment helps the model learn patterns in the data.
Can you explain how weights are initialized?
Weights can be initialized randomly or using specific techniques like Xavier or He initialization to improve training efficiency.
What happens if weights are not updated correctly?
If weights are not updated correctly, the model may fail to learn effectively, leading to poor performance and inaccurate predictions.
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