Explain feature engineering and its importance in data science projects.
Posted: Oct 14, 2025
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How do you evaluate the performance of a machine learning model?
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What is overfitting and how do you prevent it?
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Explain the bias-variance tradeoff in machine learning.
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How do you handle imbalanced datasets in classification problems?
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What is A/B testing and how do you design and analyze experiments?
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Explain dimensionality reduction techniques and when to use them.
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How do you approach time series forecasting problems?
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What is clustering and how do you choose the optimal number of clusters?
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How do you handle categorical variables in machine learning models?
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Explain ensemble methods and their advantages in machine learning.
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How do you design and implement a recommendation system?
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How do you design and implement a real-time machine learning system?
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Explain concept drift and how to handle it in production ML systems.
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How do you implement MLOps practices for scalable data science workflows?
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