Sample Machine Learning Interview Questions for Practice

Here are a few sample Machine Learning interview questions for your practice:


  • What are the different types of machine learning?
  • What is overfitting, and how to avoid it?
  • What are the “training Set” and “test Set” in a Machine Learning Model? How much data will you allocate for your training, validation, and test sets?
  • Explain the confusion matrix with respect to machine learning algorithms.
  • Write a pseudo code for a parallel implementation.
  • What data visualization tools do you use?
  • What are the three stages of building a model in machine learning?
  • Given two strings, A and B, of the same length n, find whether it is possible to cut both strings at a common point such that the first part of A and the second part of B form a palindrome.
  • How do XML and CSVs compare in terms of size?
  • What is the difference between inductive machine learning and deductive machine learning?
  • How would you build a data pipeline?
  • How is KNN different from k-means clustering?
  • What is PCA? When do you use it?
  • Will you explain your favorite algorithm in less than a minute?
  • What are type I and II errors?
  • What is a Fourier transform?
  • What is the difference between probability and likelihood?
  • What is an F1 score? How will you use it?
  • Explain the SVM algorithm in detail.
  • Which one is more important – model performance or model accuracy?
  • How is a decision tree pruned?
  • What is the difference between generative and discriminative models?
  • How will you handle an imbalanced dataset?
  • How do you ensure you’re not overfitting with a model?
  • What is a kernel trick? How is it useful?
  • What do you think of the current data process?
  • How can you use machine learning skills to generate revenue?
  • How would you implement a recommendation system for our company’s users?
  • What do you think is the most valuable data in our business?
  • How will you approach the Netflix Prize competition?
  • How do you think Google is training data for self-driving cars?
  • How would you simulate the approach AlphaGo took to beat Lee Sedol at Go?
  • What are your thoughts on GPT-3 and OpenAI’s model?
  • How do you design an email spam filter?
  • What models do you train for fun, and what GPU/hardware do you use?

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