Questions

1. Datasets in real-life projects are rarely reliable. (True|False)
2. In a real-life project, there are no missing records in a dataset. (True|False)
3. The distribution distance is the distance between two data points. (True|False)
4. Non-uniformity does not affect an ML model. (True|False)
5. Sorting by feature order can provide interesting information. (True|False)
6. Binning the x axis and the y axis in various ways offers helpful insights. (True|False)
7. The median, the minimum, and the maximum values of a feature cannot change an ML prediction. (True|False)
8. Analyzing training datasets before running an ML model is useless. It's better to wait for outputs. (True|False)
9. Facets Overview and Facets Dive can help fine-tune an ML model. (True|False)