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Updated weekly · Last refresh Sep 21

Duke Energy Machine Learning Engineer Interview Questions

The questions to prepare for a Duke Energy Machine Learning Engineer interview. Questions from real interview reports rank first. Updated daily.

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1
Machine LearningStart here. 12 questions · ~96 min
Time Series Feature EngineeringMedium

Design lag, rolling, and calendar features for a forecasting problem with temporal dependence.

Feature EngineeringSupervised LearningTime SeriesDuke Energy
Predictive Maintenance Failure ModelingHard

Design a machine learning system to predict equipment failures before they happen using sensor, event, and maintenance data.

Cross-ValidationFeature EngineeringSupervised LearningDuke Energy
Handling Overfitting in Predictive ModelsMedium

Explain how to diagnose and reduce overfitting using regularization, validation strategy, and model complexity controls.

Cross-ValidationBias-Variance TradeoffRegularizationDuke Energy
Handle Imbalanced Classification DataMedium

Build a classifier for a highly imbalanced dataset and choose metrics, sampling, and thresholds that fit the minority class.

Cross-ValidationFeature EngineeringSupervised LearningDuke Energy
Bias-Variance Tradeoff in Model SelectionEasy

Explain how bias and variance shape model complexity, generalization, and model selection.

Cross-ValidationBias-Variance TradeoffRegularizationDuke Energy
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2
More topics3 questions · ~24 min
Validate a Machine Learning ModelEasy

How to validate a machine learning model and interpret whether its metrics are trustworthy.

PrecisionAccuracyRecallDuke Energy
Optimizing for Faster ExecutionMedium

Tests your skill in performance optimization for ML training and inference.

SearchingSortingGreedyDuke Energy
Choosing Model Evaluation TechniquesEasy

Explain how you evaluate models using the right metrics, validation strategy, and error analysis for the problem.

PrecisionAccuracyRecallDuke Energy

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