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    Data Science & Analytics Q&A's are automatically generated daily after 12:00 AM through our proprietary AI-assisted system. Just like humans, AI sometimes revisits similar questions — because new data or insights can lead to different answers. Purchase tags to help expand and support the Q&A Network.

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    How can feature selection reduce overfitting in machine learning models?

    Asked on Friday, Oct 10, 2025

    Feature selection is a crucial step in the machine learning pipeline that helps reduce overfitting by eliminating irrelevant or redundant features, which can lead to a more generalized model. By focus…

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    What’s the best way to handle highly imbalanced datasets during model training?

    Asked on Thursday, Oct 09, 2025

    Handling highly imbalanced datasets is crucial for building effective models, as class imbalance can lead to biased predictions. Techniques such as resampling, using different evaluation metrics, and …

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    How do you choose the right evaluation metric when training classification models?

    Asked on Wednesday, Oct 08, 2025

    Choosing the right evaluation metric for classification models is crucial as it directly impacts the model's performance assessment and decision-making process. The choice depends on the specific prob…

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    How do you decide between batch prediction and real-time model serving for production workloads?

    Asked on Tuesday, Oct 07, 2025

    Choosing between batch prediction and real-time model serving depends on the specific requirements of your production workload, such as latency tolerance, data volume, and update frequency. Batch pred…

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