Build Your Own AI Project Worksheet

AI for students lesson 23: Design a tiny AI project · Set 481 · 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.📦 Diya collected 110 labelled messages for a spam spotter and keeps one fifth of them for testing. How many are left for training?
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.📋 Planning an AI project: which comes first — tag each photo by type or gather many examples? (a) tag each photo by type (b) gather many examples
4. 4.🧪 What is accuracy? (a) total × 2 (b) total − correct (c) correct + total (d) correct ÷ total × 100
5. 5.🎯 Aarav’s bird-song app is 90% accurate. If it is tested on 10 new bird songs, how many should it get right?
6. 6.📋 Planning an AI project: which comes first — recheck every label or choose what to sort? (a) recheck every label (b) choose what to sort
7. 7.⚖️ Two leaf identifier models were tested on the same 10 leaf photos. Model A got 10 right and Model B got 7 right. How many percentage points more accurate is Model A?
8. 8.📋 Planning an AI project: which comes first — split train and test or train the model? (a) split train and test (b) train the model
9. 9.🎯 Vihaan’s leaf identifier was tested on 20 new leaf photos and got 17 right. What is its accuracy in percent?
10. 10.❌ Ishaan’s bird-song app was tested on 19 new bird songs and got 17 right. How many did it get wrong?
11. 11.🧪 Your fruit sorter mixes up oranges and lemons. What helps most? (a) fewer examples (b) a louder speaker (c) more labelled examples (d) a new colour screen
12. 12.❌ Ishaan’s fruit sorter was tested on 20 new fruit photos and got 14 right. How many did it get wrong?
13. 13.⚖️ Two fruit sorter models were tested on the same 50 fruit photos. Model A got 34 right and Model B got 29 right. How many percentage points more accurate is Model A?
14. 14.📋 Planning an AI project: which comes first — try unseen examples or calculate percent right? (a) try unseen examples (b) calculate percent right
15. 15.🎯 Kabir’s leaf identifier is 60% accurate. If it is tested on 30 new leaf photos, how many should it get right?
16. 16.🎯 Rohan’s bird-song app is 70% accurate. If it is tested on 90 new bird songs, how many should it get right?
17. 17.📋 Planning an AI project: which comes first — correct bad labels or label each example? (a) correct bad labels (b) label each example
18. 18.🎯 Tara’s bird-song app was tested on 4 new bird songs and got 4 right. What is its accuracy in percent?
19. 19.📦 Kabir collected 160 labelled handwritten letters for a handwriting reader and keeps one fifth of them for testing. How many are left for training?
20. 20.❌ Rohan’s leaf identifier was tested on 41 new leaf photos and got 32 right. How many did it get wrong?
21. 21.🎯 Diya’s leaf identifier is 50% accurate. If it is tested on 10 new leaf photos, how many should it get right?
22. 22.🎯 Nisha’s leaf identifier is 90% accurate. If it is tested on 30 new leaf photos, how many should it get right?
23. 23.📋 Planning an AI project: which comes first — fix it and test again or train the model? (a) fix it and test again (b) train the model
24. 24.📦 Aarav collected 60 labelled messages for a spam spotter and keeps one fifth of them for testing. How many are left for training?
25. 25.📦 Diya collected 100 labelled bird songs for a bird-song app and keeps one fifth of them for testing. How many are left for training?
26. 26.🧪 Why must you test a model on examples it has NOT seen? (a) to see if it learned (b) to save paper (c) to make it faster (d) to make it bigger
27. 27.🎯 Aarav’s bird-song app was tested on 25 new bird songs and got 19 right. What is its accuracy in percent?
28. 28.📋 Planning an AI project: which comes first — correct bad labels or let it learn patterns? (a) correct bad labels (b) let it learn patterns
29. 29.🎯 Tara’s leaf identifier was tested on 4 new leaf photos and got 4 right. What is its accuracy in percent?
30. 30.🎯 Meera’s recycling sorter was tested on 5 new waste photos and got 5 right. What is its accuracy in percent?
31. 31.🎯 Meera’s recycling sorter was tested on 20 new waste photos and got 12 right. What is its accuracy in percent?
32. 32.📋 Planning an AI project: which comes first — recheck every label or try unseen examples? (a) recheck every label (b) try unseen examples
33. 33.🎯 Diya’s recycling sorter is 50% accurate. If it is tested on 70 new waste photos, how many should it get right?
34. 34.🎯 Tara’s recycling sorter is 80% accurate. If it is tested on 60 new waste photos, how many should it get right?
35. 35.📋 Planning an AI project: which comes first — work out the accuracy or split train and test? (a) work out the accuracy (b) split train and test
36. 36.📋 Planning an AI project: which comes first — correct bad labels or set aside test photos? (a) correct bad labels (b) set aside test photos
37. 37.📋 Planning an AI project: which comes first — collect fruit photos or improve data, retest? (a) collect fruit photos (b) improve data, retest
38. 38.📋 Planning an AI project: which comes first — work out the accuracy or tag each photo by type? (a) work out the accuracy (b) tag each photo by type
39. 39.📦 Rohan collected 130 labelled fruit photos for a fruit sorter and keeps one fifth of them for testing. How many are left for training?
40. 40.⚖️ Two bird-song app models were tested on the same 10 bird songs. Model A got 9 right and Model B got 8 right. How many percentage points more accurate is Model A?

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