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Helps humans see why AI made a particular choice.
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Deep learning uses many layers to solve complex tasks like image recognition.
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Removes errors, blanks, or duplicates so models learn correctly.
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Moves a trained model into apps or websites so it can make live predictions.
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CNNs scan pictures piece-by-piece to spot shapes and objects.
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Processes data locally on phones or robots instead of cloud servers.
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RNNs handle data over time, like speech or music.
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Shifts data to a similar scale with mean 0 and variance 1.