Questions

1. What is the main difference between classical computer programming and machine learning?
2. How are models classified, considering the type of target variable?
3. What are the different types of models, depending on how they learn?
4. What are the main steps when creating and using a machine learning model?
5. The output of the regression performed in Excel contains information about the residuals. What are they and how are they related to the MAE and MSE?
6. Explain underfitting and overfitting.
7. How can categorical features be used to feed machine learning models?