Build Your Own AI Project Worksheet

AI for students lesson 23: Design a tiny AI project · Set 382 · 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.📋 Planning an AI project: which comes first — calculate percent right or try unseen examples? (a) calculate percent right (b) try unseen examples
2. 2.🧪 Why must you test a model on examples it has NOT seen? (a) to save paper (b) to make it bigger (c) to make it faster (d) to see if it learned
3. 3.📋 Planning an AI project: which comes first — recheck every label or set aside test photos? (a) recheck every label (b) set aside test photos
4. 4.📋 Planning an AI project: which comes first — try unseen examples or split train and test? (a) try unseen examples (b) split train and test
5. 5.⚖️ Two handwriting reader models were tested on the same 50 handwritten letters. Model A got 48 right and Model B got 43 right. How many percentage points more accurate is Model A?
6. 6.🎯 Arjun’s spam spotter is 60% accurate. If it is tested on 60 new messages, how many should it get right?
7. 7.❌ Aarav’s recycling sorter was tested on 31 new waste photos and got 24 right. How many did it get wrong?
8. 8.📋 Planning an AI project: which comes first — try unseen examples or train the model? (a) try unseen examples (b) train the model
9. 9.📋 Planning an AI project: which comes first — label each example or try unseen examples? (a) label each example (b) try unseen examples
10. 10.⚖️ Two leaf identifier models were tested on the same 50 leaf photos. Model A got 36 right and Model B got 32 right. How many percentage points more accurate is Model A?
11. 11.🎯 Rohan’s fruit sorter is 80% accurate. If it is tested on 90 new fruit photos, how many should it get right?
12. 12.📋 Planning an AI project: which comes first — set aside test photos or label each example? (a) set aside test photos (b) label each example
13. 13.🧪 What is accuracy? (a) total × 2 (b) correct ÷ total × 100 (c) total − correct (d) correct + total
14. 14.📋 Planning an AI project: which comes first — correct bad labels or gather many examples? (a) correct bad labels (b) gather many examples
15. 15.🎯 Tara’s handwriting reader is 90% accurate. If it is tested on 40 new handwritten letters, how many should it get right?
16. 16.📋 Planning an AI project: which comes first — split train and test or choose what to sort? (a) split train and test (b) choose what to sort
17. 17.📋 Planning an AI project: which comes first — fix it and test again or set aside test photos? (a) fix it and test again (b) set aside test photos
18. 18.📋 Planning an AI project: which comes first — split train and test or tag each photo by type? (a) split train and test (b) tag each photo by type
19. 19.📦 Vihaan collected 70 labelled leaf photos for a leaf identifier and keeps one fifth of them for testing. How many are left for training?
20. 20.📋 Planning an AI project: which comes first — tag each photo by type or improve data, retest? (a) tag each photo by type (b) improve data, retest
21. 21.📋 Planning an AI project: which comes first — test on new photos or improve data, retest? (a) test on new photos (b) improve data, retest
22. 22.📋 Planning an AI project: which comes first — choose what to sort or recheck every label? (a) choose what to sort (b) recheck every label
23. 23.❌ Meera’s fruit sorter was tested on 32 new fruit photos and got 30 right. How many did it get wrong?
24. 24.🎯 Ananya’s leaf identifier was tested on 5 new leaf photos and got 3 right. What is its accuracy in percent?
25. 25.⚖️ Two recycling sorter models were tested on the same 50 waste photos. Model A got 50 right and Model B got 35 right. How many percentage points more accurate is Model A?
26. 26.📦 Arjun collected 180 labelled fruit photos for a fruit sorter and keeps one fifth of them for testing. How many are left for training?
27. 27.📋 Planning an AI project: which comes first — improve data, retest or recheck every label? (a) improve data, retest (b) recheck every label
28. 28.❌ Diya’s spam spotter was tested on 40 new messages and got 32 right. How many did it get wrong?
29. 29.🧪 Your fruit sorter mixes up oranges and lemons. What helps most? (a) more labelled examples (b) a louder speaker (c) a new colour screen (d) fewer examples
30. 30.🎯 Rohan’s recycling sorter is 90% accurate. If it is tested on 80 new waste photos, how many should it get right?
31. 31.📋 Planning an AI project: which comes first — test on new photos or fix it and test again? (a) test on new photos (b) fix it and test again
32. 32.🎯 Ishaan’s spam spotter was tested on 20 new messages and got 10 right. What is its accuracy in percent?
33. 33.📦 Kabir collected 170 labelled messages for a spam spotter and keeps one fifth of them for testing. How many are left for training?
34. 34.📋 Planning an AI project: which comes first — recheck every label or gather many examples? (a) recheck every label (b) gather many examples
35. 35.📋 Planning an AI project: which comes first — work out the accuracy or fix it and test again? (a) work out the accuracy (b) fix it and test again
36. 36.📋 Planning an AI project: which comes first — test on new photos or pick a question to solve? (a) test on new photos (b) pick a question to solve
37. 37.🎯 Tara’s fruit sorter is 50% accurate. If it is tested on 40 new fruit photos, how many should it get right?
38. 38.❌ Ananya’s handwriting reader was tested on 20 new handwritten letters and got 18 right. How many did it get wrong?
39. 39.📦 Vihaan collected 80 labelled fruit photos for a fruit sorter and keeps one fifth of them for testing. How many are left for training?
40. 40.🎯 Aarav’s leaf identifier was tested on 50 new leaf photos and got 40 right. What is its accuracy in percent?

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