Interview Q&A / Machine Learning
Machine Learning interview questions
Supervised vs unsupervised learning, overfitting, metrics and the classic models, explained simply.
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- How do you handle missing values in a dataset?
First understand why values are missing. Then drop rows or columns if few are affected, or impute with mean, median, mode, a constant, or a model-based estimate. Adding a 'was missing' flag often helps. Fit the imputer on training data only.
BeginnerQuick answer1 min read - When should you use median instead of mean to fill missing values?
Use the median when the column has outliers or is skewed, because the mean gets dragged by extreme values. Use the mean for roughly symmetric data without outliers.
BeginnerQuick answer1 min read