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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
What is the purpose of data exploration?
💡 Hint: Think about what we need before building our AI model.
Question 2
Easy
Name one task involved in data cleaning.
💡 Hint: What do we do when we find similar data entries?
Practice 4 more questions and get performance evaluation
Interactive Quizzes
Engage in quick quizzes to reinforce what you've learned and check your comprehension.
Question 1
Why is data exploration critical in the AI project cycle?
- It helps visualize data only.
- It prepares the dataset for AI modeling.
- It is not required for AI projects.
💡 Hint: Think about the importance of data in AI.
Question 2
Does data cleaning improve the dataset quality?
- True
- False
💡 Hint: Why should we remove errors from the dataset?
Solve and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
Consider a scenario where you have a massive dataset containing customer feedback. Describe the step-by-step process you would follow to explore the data effectively.
💡 Hint: Think about how to systematically approach understanding the data.
Question 2
You notice that after cleaning and exploring your data, some features seem less relevant. How would you determine whether to keep or discard these features?
💡 Hint: What criteria would you use to judge a feature's importance?
Challenge and get performance evaluation