An Artificial Neural Network (ANN) is a computational model inspired by the way human brains work. It's designed to recognize patterns and consists of interconnected nodes or "neurons".
How ANN Works
This is how the ANN works under the hood.
- Input Layer: Receives data.
- Hidden Layer(s): Processes data. There can be many.
- Output Layer: Gives final prediction or classification.
- They take in data, process it (multiply by weights, add biases), and pass the result through an activation function to produce an output.
- Data is fed into the network.
- The network makes a prediction.
- The prediction is compared to the actual value, producing an error.
- This error is used to adjust the network's weights to make better predictions next time.
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