ML Knowledge

Could you give me some examples of when overfitting and underfitting might occur in real-world scenarios? How do these impact the accuracy and performance of the model?

Machine Learning Engineer

Microsoft

SAP Concur

Sendbird

Infineon

Huawei

Qualtrics

Did you come across this question in an interview?

  • Could you give me some examples of when overfitting and underfitting might occur in real-world scenarios? How do these impact the accuracy and performance of the model?
  • Can you explain the consequences of overfitting and underfitting in real-world situations? Could you provide some examples that demonstrate when either of these might happen?
  • In which real-world scenarios do overfitting and underfitting tend to occur? How do these occurrences affect the accuracy and performance of the model?
  • Would you be able to provide me with some instances where overfitting and underfitting are common in real-world situations? What are the implications for model accuracy and performance?
  • What are some of the real-world scenarios where overfitting or underfitting can be problematic for model performance and accuracy? Can you share some examples?
  • When might overfitting and underfitting occur in a real-world setting? What are some of the effects these occurrences can have on model accuracy and performance?
  • In your experience, what are some of the examples of real-world scenarios where overfitting and underfitting have posed challenges for model performance and accuracy? What are the outcomes?
  • Could you give me some concrete examples of where overfitting and underfitting are problematic in real-world situations? What are the repercussions for the accuracy and performance of models?
  • What are some of the scenarios in which overfitting and underfitting are prevalent in real-world modelling? What are the implications of these tendencies for the accuracy and performance of the models?
  • Provide examples of real-world scenarios where overfitting and underfitting might occur, and explain the consequences of each for model performance and accuracy
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Interview question asked to Machine Learning Engineers interviewing at BetterUp, Huawei, SAP Concur and others: Could you give me some examples of when overfitting and underfitting might occur in real-world scenarios? How do these impact the accuracy and performance of the model?.