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    Why is cross-validation important for small datasets?

    Asked on Saturday, Nov 01, 2025

    Cross-validation is crucial for small datasets because it maximizes the use of limited data by providing a more reliable estimate of a model's performance. It helps in assessing how the results of a s…

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    How do you measure the drift between training and real-world data?

    Asked on Friday, Oct 31, 2025

    Measuring data drift between training and real-world data is crucial for maintaining model performance and reliability. Data drift can be quantified using statistical tests, distribution comparisons, …

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    What’s the best method for selecting features for linear regression?

    Asked on Thursday, Oct 30, 2025

    Feature selection for linear regression is crucial for improving model performance and interpretability. The best methods include using statistical techniques, regularization methods, and automated se…

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    When should you retrain a production machine learning model?

    Asked on Wednesday, Oct 29, 2025

    Retraining a production machine learning model is essential to maintain its performance and relevance as the underlying data distribution or business requirements change. This process is typically gui…

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