Mindtree – Data Science Interview Questions

Here is the list Data Science Interview Questions which are recently asked in Mindtree company. These questions are included for both Freshers and Experienced professionals. Our Data Science Training has Answered all the below Questions.

  1. Explain Eigenvalue and Eigenvector
  2. Define the term cross-validation
  3. Explain the steps for a Data analytics project
  4. Discuss Artificial Neural Networks
  5. What is Back Propagation?
  6. What is a Random Forest?
  7. What is the importance of having a selection bias?
  8. What is the K-means clustering method
  9. Explain the difference between Data Science and Data Analytics
  10. Explain p-value?
  11. What are the important libraries of Python that are used in Data Science?
  12. What does NLP stand for?
  13. What is Interpolation and Extrapolation?
  14. How can the outlier values be treated?
  15. How often should an algorithm be updated?
    16. Free PDF : Get our updated Data Science Course Content pdf
  16. Define the term deep learning
  17. Explain the method to collect and analyze data to use social media to predict the weather condition.
  18. When do you need to update the algorithm in Data science?
  19. What is Normal Distribution
  20. Which language is best for text analytics? R or Python?
  21. Explain the benefits of using statistics by Data Scientists
  22. Name various types of Deep Learning Frameworks
  23. What is skewed Distribution & uniform distribution?
  24. What is reinforcement learning?
  25. What is precision?
  26. Explain Cross-validation?
  27. Do you prefer Python or R for text analytics?
  28. What is Cluster Sampling?
  29. What tools or devices help you succeed in your role as a data scientist?
  30. Where to seek help in case of discrepancies in Tableau?
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TOP MNC's DATA SCIENCE INTERVIEW QUESTIONS & ANSWERS

Here we listed all Data Science Interview Questions and Answers which are asked in Top MNCs. Periodically we update this page with recently asked Questions, please do visit our page often and be updated in Data Science.

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