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The presented project is about investigating historic inventory marketplace info (which can be acquired from fiscal data suppliers or community APIs) in an effort to uncover temporal designs and developments.
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This project introduces collaborative filtering that implies items based on the preferences of similar end users. You may need a knowledge established that contains user-product interactions (such as, movie ratings or buy record) for developing a recommendation method.
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K-Means clustering needs details preprocessing duties like scaling numerical functions and managing lacking values.
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