Can you explain how neural networks learn patterns from data?
Sure! Neural networks learn patterns by adjusting weights through a process called training, using algorithms like backpropagation.
What is backpropagation and why is it important?
Backpropagation is an algorithm that calculates the gradient of the loss function, allowing the network to update weights effectively.
Are there different types of neural networks for pattern recognition?
Yes, there are several types, including convolutional neural networks (CNNs) for image data and recurrent neural networks (RNNs) for sequential data.
How do these networks handle complex patterns?
They use multiple layers to extract features at different levels of abstraction, enabling them to recognize complex patterns.
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