Describe overfitting and L1/L2 regularization

Quick Overview

This question evaluates understanding of model generalization and regularization techniques by probing knowledge of overfitting and L1/L2 regularization and their effects on model parameters.

Describe overfitting and L1/L2 regularization

Company: Amazon

Role: Machine Learning Engineer

Category: Machine Learning

Difficulty: easy

Interview Round: Technical Screen

Define **overfitting** in machine learning and explain why it is harmful. Then describe **L1** and **L2 regularization**: - How each one modifies the loss function. - The qualitative effect of each (e.g., sparsity, weight shrinkage). - How they help mitigate overfitting and when you might prefer one over the other.

Quick Answer: This question evaluates understanding of model generalization and regularization techniques by probing knowledge of overfitting and L1/L2 regularization and their effects on model parameters.

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Dec 8, 2025, 8:00 PM
easyMachine Learning EngineerTechnical ScreenMachine Learning
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Define overfitting in machine learning and explain why it is harmful.

Then describe L1 and L2 regularization:

  • How each one modifies the loss function.
  • The qualitative effect of each (e.g., sparsity, weight shrinkage).
  • How they help mitigate overfitting and when you might prefer one over the other.
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