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?
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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 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.
"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."
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