Statistics

Can you explain how to break down errors into bias and variance components in a machine learning model?

Machine Learning Engineer

Netflix

Avito

Waymo

Lyft

Headspace

Glovo

Did you come across this question in an interview?

Your answer

Try Free AI Interview

Google logo

Google

Product Manager

Prepare for success with realistic, role-specific interview simulations.

Product Strategy
Meta logo

Meta

Product Manager

Prepare for success with realistic, role-specific interview simulations.

Product Sense
Meta logo

Meta

Engineering Manager

Prepare for success with realistic, role-specific interview simulations.

System Design
Amazon logo

Amazon

Data Scientist

Prepare for success with realistic, role-specific interview simulations.

Behavioral
  • Can you explain how to break down errors into bias and variance components in a machine learning model?
  • How can we assess if a model is suffering from high bias or high variance?
  • Could you elaborate on ways to decompose errors into variance and bias?
  • Would you mind explaining how to distinguish between variance and bias in a model's errors?
  • Could you provide an explanation of how to split up errors into bias and variance categories in a predictive model?
  • Walk me through the process of differentiating between high variance and high bias in a machine learning model.
  • Can you give an overview of how a model can be evaluated for bias and variance errors?
  • Can you describe an approach for breaking down errors in a machine learning model into bias and variance components?
  • Can you discuss the steps involved in decomposing errors into bias and variance in a machine learning model?
  • How to decompose errors into variance and bias?

Interview question asked to Machine Learning Engineers interviewing at Monzo, Roblox, Mastercard and others: Can you explain how to break down errors into bias and variance components in a machine learning model?.