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2. In spam detection, the AI problem is to:

a) Send emails b) Write emails
c) Delete all emails d) Identify spam emails

3. The first stage of a project cycle is:

a) Defining the problem b) Data collection

c) Model development d) Model deployment

4. If an AI model predicts 8 out of 10 spam emails, the accuracy of the model is:

a) 50% b) 20%

c) 80% d) 100%

5. AI model improves because:

a) It thinks like a human b) It has feelings

c) New data is added d) It gets angry

B. Fill in the blanks.
1. AI learns by finding in data.

2. An AI project follows a cycle.

3. Spam emails often contain suspicious .
4. After testing, we the system.

5. AI cannot work without .

C. Short answer questions.

1. How does AI learn?
2. Why is defining the problem important in an AI project?

3. What happens in the testing stage of an AI project?
4. What is meant by accuracy in AI?
5. Give one real-life example of an AI project.

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