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 does the K-Nearest Neighbours algorithm make a prediction?
KNN stores all training data. To predict, it finds the k training points closest to the new point and takes a majority vote (classification) or an average (regression) of their targets.
BeginnerQuick answer1 min read - What is the difference between Euclidean and Manhattan distance, and which should KNN use?
Euclidean is the straight-line distance, sqrt of the sum of squared differences. Manhattan is the sum of absolute differences, like walking along city blocks. Euclidean is the default; Manhattan can be better in high dimensions or with many outliers.
BeginnerQuick answer1 min read