1. Difference between bagging and boosting.
2. Explain Random Forest.
3. How does Random Forest reduce the variance?
4. How does XG boost algorithm work?
5. What is a Support Vector Machine?
6. What are the types of kernels?
7. Difference between polynomial kernel and RBF Kernel?
8. Which is better? Count Vectorizer or TF-IDF?
9. What is word2vec?
10. Give an example of precision and recall.
11. Difference between linear regression and logistic regression?
12. How can you draw a best-fit line in linear regression?
13. What is multicolinearity?

Question

1. Difference between bagging and boosting.
2. Explain Random Forest.
3. How does Random Forest reduce the variance?
4. How does XG boost algorithm work?
5. What is a Support Vector Machine?
6. What are the types of kernels? 
7. Difference between polynomial kernel and RBF Kernel?
8. Which is better? Count Vectorizer or TF-IDF?
9. What is word2vec?
10. Give an example of precision and recall.
11. Difference between linear regression and logistic regression?
12. How can you draw a best-fit line in linear regression?
13. What is multicolinearity?

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