Machine Learning Mock Interview

Practice 20 Machine Learning interview questions covering algorithms, model evaluation, and deep learning fundamentals.

Question 3 of 20

Can you briefly discuss the trade-offs between bias and variance?

How to Answer
Example Answer
Community Answers

William Swansen has worked in the employment assistance realm since 2007. He is an author, job search strategist, and career advisor who helps individuals worldwide and in various professions to find their ideal careers.

This is an example of a technical question. When interviewing for a machine learning engineer's role, the majority of the interview will consist of technical questions. Like operational questions, technical questions are best answered directly and succinctly. You begin by defining the terms addressed in the question and, in this case, compare them. You may also want to give an example of how you use the concept in your work.

William Swansen

"Bias error is usually the result of over-simplifying your assumptions in a learning algorithm. This reduces the predictive accuracy of the model. Variance, on the other hand, results from too much complexity in the learning algorithm. This results in the algorithm dismissing important data, and your results being skewed. The key to developing a good learning algorithm is to use a balance between bias and variance."

Write Your Answer

0 - Character Count

Unlock All 20 Machine Learning Questions

Unlock expert responses to technical questions that separate ML candidates from data scientists.

Get Started

Previous Question Next Question