1. What is mean and median
2. Difference between normal and gaussian
distribution
3. What is central limit theorem
4. What is null hypothesis
5. What is confidence interval
6. What is covariance and correlation and how will u
interpret it.
7. How will you find out the outliers in the dataset
and is it always to remove outliers
8. Explain about Machine Learning
9. Explain the algorithm of your choice
10. Different methods of missing values imputation
11. Explain me your ml project
12. How did you handle imbalance dataset
13. What is stratified samplings
14. Difference between standard scalar and normal
scalar
15. Different type of visualization in Dl project
16. What architecture have you used
17. Why have u not used RNN in your nlp project
18. Why we don’t prefer CNN in nlp based project
19 What is exploding gradient and vanishing gradient and how to rectify it
20. Difference between LSTM and GRU
21. What is precision and recall
22 What is auc metic
23. What if your precision and recall are same
Date: 13/06/21
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