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Preprocessing is key: handle missing values, scale features, and split data into training and testing sets. After training, evaluate your model with appropriate metrics. Need improvement? Tune hyperparameters or try a different approach. Asking for help with machine learning assignment is smart—sometimes a fresh perspective makes things much easier!