Data Collection Quiz

Quiz covering ML Development Lifecycle

Questions in this quiz

A preview of the 5 questions covered. Start the quiz above to answer them, check your score, and read the explanations.

1. 1

   In the context of the ML development lifecycle, what is the primary purpose of data collection?

2. 2

   Why is it important to ensure data diversity during the collection phase?

3. 3

   You are building a model to detect fraudulent credit card transactions. You notice your dataset contains 99% legitimate transactions and only 1% fraudulent ones. What is this issue called?

4. 4

   Which of the following is a common risk associated with using 'web scraping' as a method for data collection?

5. 5

   During data collection, you inadvertently include 'future' information in your training set that would not be available at the time of prediction. What is this phenomenon called?