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Crop prediction is the process of forecasting the yield or production of crops for a given period, based on historical data, weather patterns, and other relevant factors. The prediction can be used to inform decisions regarding planting, harvesting, and marketing of crops. Machine learning and artificial intelligence techniques are increasingly being used to improve crop prediction accuracy. These techniques use algorithms to analyze large amounts of data, such as weather patterns, soil conditions, and crop history, to make predictions about future crop yields. Crop prediction models can be used by farmers, agribusinesses, and governments to optimize crop management, reduce waste, and maximize profits. Accurate crop prediction can also help to mitigate the impact of climate change on agricultural production by enabling farmers to adapt to changing weather patterns and other environmental factors

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