Questions
Answer the following questions to test your knowledge of this chapter:
- What are some of the main ways of collecting datasets for a data science project?
- Can Git LFS be used with Git? If so, what is the overall process?
- Which type of attribute can have its missing values filled out with the mean? What about the mode?
- What problem does one-hot encoding address? What problem can arise from using one-hot encoding?
- Which type of attribute can benefit from bar charts? What about distribution plots?
- Why is it important to consider the feature correlation matrix for a dataset?
- Aside from predictive tasks, what can we use ML models for (like we did in this chapter)?
