Machine Learning Engineer
Machine learning questions
28 questions on Machine learning for machine learning engineers, easiest first.
Easy 14
- Big gap between train and validation accuracyeasy
- Which model needs feature scalingeasy
- Encoding a city featureeasy
- Bias and variance as complexity growseasy
- Accuracy on imbalanced dataeasy
- What logistic regression outputseasy
- k-nearest neighbours voteeasy
- What k-means minimiseseasy
- Variance kept by two componentseasy
- Gini impurity of a nodeeasy
- Why random forests average treeseasy
- Dropout after eval()easy
- Standardising a single valueeasy
- When early stopping triggerseasy
Medium 9
- Scaling before splittingmedium
- Handling class imbalancemedium
- Which regularisation gives sparse weightsmedium
- Millions of product IDs as a featuremedium
- Reading a logistic regression weightmedium
- Precision at 5 for a ranked listmedium
- Random search versus grid searchmedium
- Raising C in a soft-margin SVMmedium
- Target encoding without leakagemedium