AI and machine learning
0 of 9 solved
9 questions
- Train, validation and test sets — and data leakageModel evaluationEasyConceptual
- Classification vs regression: losses and metricsSupervised learningEasyConceptual
- Gradient descent and the learning rateOptimisationEasyConceptual
- Bias–variance trade-offModel evaluationMediumConceptual
- Precision, recall and F1 for a spam filterEvaluation metricsMediumNumerical
- L1 vs L2 regularisationRegularisationMediumConceptual
- Bagging vs boosting (random forest vs gradient boosting)Ensemble methodsMediumConceptual
- Vanishing and exploding gradients in deep networksDeep learningHardConceptual
- Self-attention in transformersDeep learning architecturesHardConceptual