Do you think that treating a categorical variable as a continuous variable would result in a better predictive model?
How will you explain machine learning to a layperson in an easily comprehensible manner?
What is svm algorithm?
Tell us why is “naive” bayes naive?
When does regularization become necessary in machine learning?
What is unsupervised learning?
What is supervised versus unsupervised learning?
Explain how do you think google is training data for self-driving cars?
Tell us what is decision tree classification?
Tell us what kind of problems does regularization solve?
Can you explain what is the difference between inductive machine learning and deductive machine learning?
What sentiment analysis?
What is feature engineering?
How to decide one problem is a machine learning problem or not?
Do you know what is kernel svm?