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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- What is overfitting and underfitting, and what is the bias-variance trade-off?
Overfitting means the model memorises the training data, including noise, so it does well in training but badly on new data. Underfitting means the model is too simple to learn the pattern at all. The bias-variance trade-off is the balance between these two errors.
BeginnerIn-depth4 min read - How do you choose k in KNN, and what happens when k is very small or very large?
Small k (like 1) follows noise and overfits; very large k smooths too much and underfits, at the extreme predicting the majority class for everything. Choose k by cross-validation, and use an odd k for two-class problems to avoid ties.
BeginnerQuick answer1 min read