Machine Learning Interview Questions and Answers: https://www.springboard.com/blog/machine-learning-interview-questions
- What’s the trade-off between bias and variance?
- What is the difference between supervised and unsupervised machine learning?
- How is KNN different from k-means clustering?
- Explain how a ROC curve works.
- Define precision and recall
- What is Bayes’ Theorem? How is it useful in a machine learning context?
- Why is “Naive” Bayes naive?
- Explain the difference between L1 and L2 regularization
- What’s your favorite algorithm, and can you explain it to me in less than a minute?
- What’s the difference between Type I and Type II error?
- What’s a Fourier transform?
More and answers: https://www.springboard.com/blog/machine-learning-interview-questions