Build Your Own AI Project Worksheet

AI for students lesson 23: Design a tiny AI project · Set 809 · 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.🎯 Aarav’s leaf identifier was tested on 50 new leaf photos and got 26 right. What is its accuracy in percent?
2. 2.🎯 Ananya’s leaf identifier is 90% accurate. If it is tested on 70 new leaf photos, how many should it get right?
3. 3.📋 Planning an AI project: which comes first — correct bad labels or choose what to sort? (a) correct bad labels (b) choose what to sort
4. 4.🧪 You can plan a simple AI project with… (a) only a big robot (b) paper and examples (c) nothing at all (d) a secret password
5. 5.📦 Arjun collected 180 labelled fruit photos for a fruit sorter and keeps one fifth of them for testing. How many are left for training?
6. 6.📦 Meera collected 40 labelled leaf photos for a leaf identifier and keeps one fifth of them for testing. How many are left for training?
7. 7.📋 Planning an AI project: which comes first — calculate percent right or test on new photos? (a) calculate percent right (b) test on new photos
8. 8.❌ Aarav’s leaf identifier was tested on 25 new leaf photos and got 23 right. How many did it get wrong?
9. 9.📦 Saanvi collected 70 labelled handwritten letters for a handwriting reader and keeps one fifth of them for testing. How many are left for training?
10. 10.📦 Tara collected 120 labelled handwritten letters for a handwriting reader and keeps one fifth of them for testing. How many are left for training?
11. 11.🧪 What is accuracy? (a) total − correct (b) total × 2 (c) correct ÷ total × 100 (d) correct + total
12. 12.⚖️ Two recycling sorter models were tested on the same 10 waste photos. Model A got 10 right and Model B got 6 right. How many percentage points more accurate is Model A?
13. 13.🎯 Meera’s recycling sorter was tested on 25 new waste photos and got 16 right. What is its accuracy in percent?
14. 14.⚖️ Two fruit sorter models were tested on the same 20 fruit photos. Model A got 19 right and Model B got 17 right. How many percentage points more accurate is Model A?
15. 15.📋 Planning an AI project: which comes first — try unseen examples or fix it and test again? (a) try unseen examples (b) fix it and test again
16. 16.📋 Planning an AI project: which comes first — collect fruit photos or choose what to sort? (a) collect fruit photos (b) choose what to sort
17. 17.⚖️ Two handwriting reader models were tested on the same 25 handwritten letters. Model A got 21 right and Model B got 14 right. How many percentage points more accurate is Model A?
18. 18.🧪 Why must you test a model on examples it has NOT seen? (a) to save paper (b) to make it faster (c) to make it bigger (d) to see if it learned
19. 19.📋 Planning an AI project: which comes first — train the model or label each example? (a) train the model (b) label each example
20. 20.❌ Aarav’s fruit sorter was tested on 19 new fruit photos and got 15 right. How many did it get wrong?
21. 21.⚖️ Two fruit sorter models were tested on the same 25 fruit photos. Model A got 24 right and Model B got 23 right. How many percentage points more accurate is Model A?
22. 22.📋 Planning an AI project: which comes first — test on new photos or split train and test? (a) test on new photos (b) split train and test
23. 23.🧪 Your fruit sorter mixes up oranges and lemons. What helps most? (a) a new colour screen (b) more labelled examples (c) a louder speaker (d) fewer examples
24. 24.🎯 Ishaan’s bird-song app is 60% accurate. If it is tested on 40 new bird songs, how many should it get right?
25. 25.⚖️ Two fruit sorter models were tested on the same 20 fruit photos. Model A got 20 right and Model B got 17 right. How many percentage points more accurate is Model A?
26. 26.🎯 Vihaan’s handwriting reader is 70% accurate. If it is tested on 60 new handwritten letters, how many should it get right?
27. 27.❌ Ishaan’s fruit sorter was tested on 17 new fruit photos and got 14 right. How many did it get wrong?
28. 28.📋 Planning an AI project: which comes first — fix it and test again or gather many examples? (a) fix it and test again (b) gather many examples
29. 29.📋 Planning an AI project: which comes first — pick a question to solve or test on new photos? (a) pick a question to solve (b) test on new photos
30. 30.📋 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
31. 31.📋 Planning an AI project: which comes first — try unseen examples or work out the accuracy? (a) try unseen examples (b) work out the accuracy
32. 32.📦 Nisha collected 60 labelled fruit photos for a fruit sorter and keeps one fifth of them for testing. How many are left for training?
33. 33.🎯 Rohan’s leaf identifier was tested on 4 new leaf photos and got 2 right. What is its accuracy in percent?
34. 34.❌ Rohan’s recycling sorter was tested on 24 new waste photos and got 17 right. How many did it get wrong?
35. 35.📋 Planning an AI project: which comes first — recheck every label or fix it and test again? (a) recheck every label (b) fix it and test again
36. 36.🎯 Aarav’s handwriting reader is 90% accurate. If it is tested on 80 new handwritten letters, how many should it get right?
37. 37.📋 Planning an AI project: which comes first — choose what to sort or recheck every label? (a) choose what to sort (b) recheck every label
38. 38.🎯 Meera’s fruit sorter was tested on 10 new fruit photos and got 10 right. What is its accuracy in percent?
39. 39.❌ Diya’s bird-song app was tested on 29 new bird songs and got 20 right. How many did it get wrong?
40. 40.🎯 Nisha’s leaf identifier is 70% accurate. If it is tested on 70 new leaf photos, how many should it get right?

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