How do I approach Machine Learning interview questions?

Machine Learning questions require understanding of core concepts and practice. PracHub provides solutions with explanations to help you master machine learning interviews.

What difficulty level is this interview question?

This is a medium difficulty Machine Learning question, commonly asked during Onsite rounds at Snapchat.

What role is this question designed for?

This question is commonly asked for Machine Learning Engineer candidates at Snapchat during technical interviews.

Explain Core ML Concepts | Snapchat Interview Question

Explain Core ML Concepts

Last updated: Apr 22, 2026

Quick Overview

This question evaluates understanding of foundational machine learning and deep learning concepts, including the bias–variance decomposition, differences between batch normalization and layer normalization, and the causes of vanishing gradients.

Snapchat

Feb 2, 2026, 12:00 AM

Machine Learning Engineer

Onsite

Machine Learning

You are interviewing for a machine learning role. Answer the following core questions:

Explain the bias-variance decomposition of prediction error and how it relates to underfitting and overfitting.
Compare batch normalization and layer normalization: how each is computed, where each works well, and their trade-offs.
Explain why vanishing gradients happen in deep neural networks and describe practical ways to mitigate them.

Solution

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