Build Your Own AI Project Worksheet

AI for students lesson 23: Design a tiny AI project · Set 689 · 40 questions

AI tip (Accuracy = correct ÷ total × 100): Steps: 1 choose a problem → 2 collect examples → 3 label them → 4 check and correct bad labels (clean the data) → 5 split into training and test sets → 6 train → 7 test with new examples → 8 measure accuracy → 9 improve the data and retest. Accuracy = correct ÷ total × 100. Wrong = total − correct. Expected right = accuracy ÷ 100 × total. Keep some examples apart for testing (for example one fifth); the rest are for training.

1. 1.🧪 Why must you test a model on examples it has NOT seen? (a) to see if it learned (b) to make it faster (c) to save paper (d) to make it bigger
2. 2.📋 Planning an AI project: which comes first — work out the accuracy or try unseen examples? (a) work out the accuracy (b) try unseen examples
3. 3.🎯 Ishaan’s fruit sorter is 50% accurate. If it is tested on 80 new fruit photos, how many should it get right?
4. 4.❌ Ananya’s spam spotter was tested on 41 new messages and got 32 right. How many did it get wrong?
5. 5.⚖️ Two leaf identifier models were tested on the same 50 leaf photos. Model A got 50 right and Model B got 41 right. How many percentage points more accurate is Model A?
6. 6.📋 Planning an AI project: which comes first — pick a question to solve or correct bad labels? (a) pick a question to solve (b) correct bad labels
7. 7.🎯 Nisha’s fruit sorter was tested on 10 new fruit photos and got 7 right. What is its accuracy in percent?
8. 8.❌ Arjun’s handwriting reader was tested on 32 new handwritten letters and got 30 right. How many did it get wrong?
9. 9.❌ Ananya’s recycling sorter was tested on 26 new waste photos and got 18 right. How many did it get wrong?
10. 10.🎯 Tara’s fruit sorter is 60% accurate. If it is tested on 90 new fruit photos, how many should it get right?
11. 11.⚖️ Two fruit sorter models were tested on the same 20 fruit photos. Model A got 17 right and Model B got 16 right. How many percentage points more accurate is Model A?
12. 12.🎯 Kabir’s recycling sorter was tested on 25 new waste photos and got 18 right. What is its accuracy in percent?
13. 13.🧪 What is accuracy? (a) total − correct (b) total × 2 (c) correct ÷ total × 100 (d) correct + total
14. 14.📋 Planning an AI project: which comes first — correct bad labels or test on new photos? (a) correct bad labels (b) test on new photos
15. 15.📋 Planning an AI project: which comes first — tag each photo by type or let it learn patterns? (a) tag each photo by type (b) let it learn patterns
16. 16.⚖️ Two leaf identifier models were tested on the same 10 leaf photos. Model A got 8 right and Model B got 5 right. How many percentage points more accurate is Model A?
17. 17.📋 Planning an AI project: which comes first — split train and test or pick a question to solve? (a) split train and test (b) pick a question to solve
18. 18.🧪 You can plan a simple AI project with… (a) only a big robot (b) a secret password (c) paper and examples (d) nothing at all
19. 19.📋 Planning an AI project: which comes first — tag each photo by type or set aside test photos? (a) tag each photo by type (b) set aside test photos
20. 20.❌ Arjun’s recycling sorter was tested on 25 new waste photos and got 20 right. How many did it get wrong?
21. 21.🎯 Meera’s recycling sorter was tested on 4 new waste photos and got 3 right. What is its accuracy in percent?
22. 22.❌ Ananya’s spam spotter was tested on 32 new messages and got 27 right. How many did it get wrong?
23. 23.📋 Planning an AI project: which comes first — tag each photo by type or choose what to sort? (a) tag each photo by type (b) choose what to sort
24. 24.📋 Planning an AI project: which comes first — test on new photos or gather many examples? (a) test on new photos (b) gather many examples
25. 25.📋 Planning an AI project: which comes first — work out the accuracy or improve data, retest? (a) work out the accuracy (b) improve data, retest
26. 26.🎯 Nisha’s handwriting reader is 60% accurate. If it is tested on 80 new handwritten letters, how many should it get right?
27. 27.📦 Tara collected 120 labelled bird songs for a bird-song app and keeps one fifth of them for testing. How many are left for training?
28. 28.❌ Ananya’s recycling sorter was tested on 28 new waste photos and got 19 right. How many did it get wrong?
29. 29.🧪 Your fruit sorter mixes up oranges and lemons. What helps most? (a) a louder speaker (b) fewer examples (c) more labelled examples (d) a new colour screen
30. 30.⚖️ Two handwriting reader models were tested on the same 25 handwritten letters. Model A got 25 right and Model B got 21 right. How many percentage points more accurate is Model A?
31. 31.📋 Planning an AI project: which comes first — fix it and test again or try unseen examples? (a) fix it and test again (b) try unseen examples
32. 32.❌ Vihaan’s fruit sorter was tested on 33 new fruit photos and got 24 right. How many did it get wrong?
33. 33.🎯 Vihaan’s handwriting reader is 50% accurate. If it is tested on 40 new handwritten letters, how many should it get right?
34. 34.📋 Planning an AI project: which comes first — recheck every label or work out the accuracy? (a) recheck every label (b) work out the accuracy
35. 35.📋 Planning an AI project: which comes first — choose what to sort or gather many examples? (a) choose what to sort (b) gather many examples
36. 36.📋 Planning an AI project: which comes first — split train and test or improve data, retest? (a) split train and test (b) improve data, retest
37. 37.⚖️ Two spam spotter models were tested on the same 25 messages. Model A got 14 right and Model B got 13 right. How many percentage points more accurate is Model A?
38. 38.📋 Planning an AI project: which comes first — gather many examples or split train and test? (a) gather many examples (b) split train and test
39. 39.📋 Planning an AI project: which comes first — set aside test photos or improve data, retest? (a) set aside test photos (b) improve data, retest
40. 40.🎯 Aarav’s fruit sorter was tested on 5 new fruit photos and got 5 right. What is its accuracy in percent?

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