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Machine learning models rely nous-mêmes numerical representations of data to identify modèle and make predictions. However, raw data often contains noise, irrelevant information, pépite missing values that can degrade model performance. Feature engineering in ML appui in:This fonte of learning is based je trial and error. Instead of learning fro