Build Your Own AI Project Worksheet

AI for students lesson 23: Design a tiny AI project · Set 937 · 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.🎯 Nisha’s leaf identifier was tested on 20 new leaf photos and got 17 right. What is its accuracy in percent?
2. 2.🧪 What is accuracy? (a) total × 2 (b) total − correct (c) correct ÷ total × 100 (d) correct + total
3. 3.⚖️ Two bird-song app models were tested on the same 10 bird songs. Model A got 9 right and Model B got 5 right. How many percentage points more accurate is Model A?
4. 4.📋 Planning an AI project: which comes first — work out the accuracy or test on new photos? (a) work out the accuracy (b) test on new photos
5. 5.❌ Nisha’s bird-song app was tested on 16 new bird songs and got 15 right. How many did it get wrong?
6. 6.📋 Planning an AI project: which comes first — train the model or tag each photo by type? (a) train the model (b) tag each photo by type
7. 7.📦 Nisha collected 60 labelled bird songs for a bird-song app and keeps one fifth of them for testing. How many are left for training?
8. 8.📋 Planning an AI project: which comes first — try unseen examples or set aside test photos? (a) try unseen examples (b) set aside test photos
9. 9.📋 Planning an AI project: which comes first — try unseen examples or improve data, retest? (a) try unseen examples (b) improve data, retest
10. 10.🎯 Rohan’s recycling sorter is 70% accurate. If it is tested on 40 new waste photos, how many should it get right?
11. 11.🧪 Your fruit sorter mixes up oranges and lemons. What helps most? (a) more labelled examples (b) a new colour screen (c) fewer examples (d) a louder speaker
12. 12.🎯 Saanvi’s spam spotter was tested on 4 new messages and got 4 right. What is its accuracy in percent?
13. 13.🧪 Why must you test a model on examples it has NOT seen? (a) to save paper (b) to see if it learned (c) to make it faster (d) to make it bigger
14. 14.⚖️ Two spam spotter models were tested on the same 20 messages. Model A got 20 right and Model B got 19 right. How many percentage points more accurate is Model A?
15. 15.🧪 You can plan a simple AI project with… (a) a secret password (b) nothing at all (c) only a big robot (d) paper and examples
16. 16.🎯 Nisha’s fruit sorter was tested on 10 new fruit photos and got 6 right. What is its accuracy in percent?
17. 17.⚖️ Two handwriting reader models were tested on the same 50 handwritten letters. Model A got 46 right and Model B got 34 right. How many percentage points more accurate is Model A?
18. 18.📋 Planning an AI project: which comes first — calculate percent right or tag each photo by type? (a) calculate percent right (b) tag each photo by type
19. 19.📦 Kabir collected 70 labelled fruit photos for a fruit sorter and keeps one fifth of them for testing. How many are left for training?
20. 20.📋 Planning an AI project: which comes first — label each example or collect fruit photos? (a) label each example (b) collect fruit photos
21. 21.📋 Planning an AI project: which comes first — test on new photos or calculate percent right? (a) test on new photos (b) calculate percent right
22. 22.⚖️ Two recycling sorter models were tested on the same 50 waste photos. Model A got 30 right and Model B got 26 right. How many percentage points more accurate is Model A?
23. 23.⚖️ Two spam spotter models were tested on the same 25 messages. Model A got 24 right and Model B got 14 right. How many percentage points more accurate is Model A?
24. 24.🎯 Vihaan’s spam spotter is 50% accurate. If it is tested on 100 new messages, how many should it get right?
25. 25.📦 Meera collected 180 labelled leaf photos for a leaf identifier and keeps one fifth of them for testing. How many are left for training?
26. 26.📋 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
27. 27.⚖️ Two bird-song app models were tested on the same 10 bird songs. Model A got 8 right and Model B got 5 right. How many percentage points more accurate is Model A?
28. 28.📋 Planning an AI project: which comes first — calculate percent right or improve data, retest? (a) calculate percent right (b) improve data, retest
29. 29.🎯 Nisha’s handwriting reader is 80% accurate. If it is tested on 50 new handwritten letters, how many should it get right?
30. 30.🎯 Nisha’s handwriting reader is 90% accurate. If it is tested on 30 new handwritten letters, how many should it get right?
31. 31.📦 Rohan collected 190 labelled waste photos for a recycling sorter and keeps one fifth of them for testing. How many are left for training?
32. 32.🎯 Ishaan’s bird-song app is 70% accurate. If it is tested on 80 new bird songs, how many should it get right?
33. 33.📋 Planning an AI project: which comes first — correct bad labels or collect fruit photos? (a) correct bad labels (b) collect fruit photos
34. 34.📋 Planning an AI project: which comes first — split train and test or improve data, retest? (a) split train and test (b) improve data, retest
35. 35.📋 Planning an AI project: which comes first — tag each photo by type or train the model? (a) tag each photo by type (b) train the model
36. 36.📦 Saanvi collected 40 labelled bird songs for a bird-song app and keeps one fifth of them for testing. How many are left for training?
37. 37.❌ Kabir’s fruit sorter was tested on 39 new fruit photos and got 37 right. How many did it get wrong?
38. 38.🎯 Ananya’s fruit sorter was tested on 25 new fruit photos and got 13 right. What is its accuracy in percent?
39. 39.📋 Planning an AI project: which comes first — tag each photo by type or split train and test? (a) tag each photo by type (b) split train and test
40. 40.📦 Arjun collected 150 labelled leaf photos for a leaf identifier and keeps one fifth of them for testing. How many are left for training?

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