1. How do you interpret weights and biases in the case of SVM? 2. How do you interpret coefficients (B0, B1, B2) in the case of regression? 3. What is the calculation inside the AD Fuller stationarity test? What is the unit root? 4. How is time series different from regression apart from regressing dependent variables with past values? Why is regression interpolation and time-series extrapolation? 5. What is an abstract class in python? How do you use functions from an abstract class into another class? 6. Which APIs have you used? How? 7. What would be a technical fault if the stationarity is not present in the series 8. Difference between assumptions of a time series and regression? 9. Which type of loss would you use in a classification problem? Hinge or what? 10. How is Ada boost different from XGBoost? 11. What is the kernel trick in SVM?
