Module 11 Self-Test
- Walk through a Fermi estimate for "How many pizza deliveries happen in Chicago per day?"
- Tabular data: deep learning or gradient boosting? Why?
- How does converting a string column to category type save memory?
- Expected rolls to see all 6 die faces?
- What's a star schema? Name the two types of tables.
- Bayes — a defective item from a two-machine factory. Can you set up the formula without looking?
Practice Questions
Q: Walk through a Fermi estimate for "How many pizza deliveries happen in Chicago per day?"
Q: Tabular data: deep learning or gradient boosting? Why?
Q: How does converting a string column to category type save memory?
Q: Expected rolls to see all 6 die faces?
Q: What's a star schema? Name the two types of tables.
Q: Bayes — a defective item from a two-machine factory. Can you set up the formula without looking?