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How do neural networks work?
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Neural networks are machine learning algorithms that imitate the structure and functioning of the human brain. They are composed of layers of interconnected nodes, each of which performs a calculation on an input, with the output of each node becoming the input of the next layer. The input layer receives the input data, such as images, audio, or text. Each successive layer processes and distills the input data until a final output layer produces the desired result, such as predicting the sentiment of a sentence or recognizing an image.