In the context of neural networks, what is the role of a hidden layer?
- It stores the input data
- It performs the final prediction
- It extracts and transforms features
- It provides feedback to the user
The role of a hidden layer in a neural network is to extract and transform features from the input data. Hidden layers learn to represent the data in a way that makes it easier for the network to make predictions or classifications. They are essential for capturing the underlying patterns and relationships in the data.
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