Build Your Own AI Project Worksheet

AI for students lesson 23: Design a tiny AI project · Set 943 · 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.❌ Arjun’s leaf identifier was tested on 23 new leaf photos and got 18 right. How many did it get wrong?
2. 2.📦 Vihaan collected 60 labelled waste photos for a recycling sorter and keeps one fifth of them for testing. How many are left for training?
3. 3.🎯 Tara’s fruit sorter is 70% accurate. If it is tested on 40 new fruit photos, how many should it get right?
4. 4.📋 Planning an AI project: which comes first — work out the accuracy or try unseen examples? (a) work out the accuracy (b) try unseen examples
5. 5.⚖️ Two leaf identifier models were tested on the same 25 leaf photos. Model A got 21 right and Model B got 19 right. How many percentage points more accurate is Model A?
6. 6.📋 Planning an AI project: which comes first — label each example or train the model? (a) label each example (b) train the model
7. 7.🧪 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
8. 8.🎯 Ishaan’s recycling sorter was tested on 50 new waste photos and got 27 right. What is its accuracy in percent?
9. 9.🎯 Nisha’s fruit sorter is 70% accurate. If it is tested on 70 new fruit photos, how many should it get right?
10. 10.📦 Diya collected 140 labelled bird songs for a bird-song app and keeps one fifth of them for testing. How many are left for training?
11. 11.📋 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
12. 12.🧪 What is accuracy? (a) total × 2 (b) total − correct (c) correct + total (d) correct ÷ total × 100
13. 13.📦 Arjun collected 200 labelled waste photos for a recycling sorter and keeps one fifth of them for testing. How many are left for training?
14. 14.🧪 Your fruit sorter mixes up oranges and lemons. What helps most? (a) a louder speaker (b) a new colour screen (c) fewer examples (d) more labelled examples
15. 15.⚖️ Two leaf identifier models were tested on the same 10 leaf photos. Model A got 10 right and Model B got 9 right. How many percentage points more accurate is Model A?
16. 16.📋 Planning an AI project: which comes first — gather many examples or train the model? (a) gather many examples (b) train the model
17. 17.🎯 Vihaan’s leaf identifier is 70% accurate. If it is tested on 100 new leaf photos, how many should it get right?
18. 18.📦 Kabir collected 40 labelled bird songs for a bird-song app and keeps one fifth of them for testing. How many are left for training?
19. 19.❌ Aarav’s leaf identifier was tested on 44 new leaf photos and got 39 right. How many did it get wrong?
20. 20.📋 Planning an AI project: which comes first — fix it and test again or work out the accuracy? (a) fix it and test again (b) work out the accuracy
21. 21.📋 Planning an AI project: which comes first — fix it and test again or test on new photos? (a) fix it and test again (b) test on new photos
22. 22.🎯 Ishaan’s bird-song app is 50% accurate. If it is tested on 70 new bird songs, how many should it get right?
23. 23.⚖️ Two leaf identifier models were tested on the same 25 leaf photos. Model A got 19 right and Model B got 17 right. How many percentage points more accurate is Model A?
24. 24.📦 Ananya collected 50 labelled handwritten letters for a handwriting reader and keeps one fifth of them for testing. How many are left for training?
25. 25.📦 Kabir collected 200 labelled handwritten letters for a handwriting reader and keeps one fifth of them for testing. How many are left for training?
26. 26.❌ Saanvi’s recycling sorter was tested on 18 new waste photos and got 16 right. How many did it get wrong?
27. 27.🧪 You can plan a simple AI project with… (a) a secret password (b) only a big robot (c) nothing at all (d) paper and examples
28. 28.🎯 Rohan’s spam spotter was tested on 5 new messages and got 4 right. What is its accuracy in percent?
29. 29.📋 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
30. 30.📋 Planning an AI project: which comes first — correct bad labels or let it learn patterns? (a) correct bad labels (b) let it learn patterns
31. 31.⚖️ Two bird-song app models were tested on the same 20 bird songs. Model A got 20 right and Model B got 19 right. How many percentage points more accurate is Model A?
32. 32.🎯 Arjun’s leaf identifier was tested on 10 new leaf photos and got 5 right. What is its accuracy in percent?
33. 33.📋 Planning an AI project: which comes first — work out the accuracy or set aside test photos? (a) work out the accuracy (b) set aside test photos
34. 34.⚖️ Two spam spotter models were tested on the same 50 messages. Model A got 41 right and Model B got 36 right. How many percentage points more accurate is Model A?
35. 35.📦 Nisha collected 130 labelled messages for a spam spotter and keeps one fifth of them for testing. How many are left for training?
36. 36.📋 Planning an AI project: which comes first — set aside test photos or pick a question to solve? (a) set aside test photos (b) pick a question to solve
37. 37.📋 Planning an AI project: which comes first — work out the accuracy or let it learn patterns? (a) work out the accuracy (b) let it learn patterns
38. 38.❌ Arjun’s handwriting reader was tested on 36 new handwritten letters and got 27 right. How many did it get wrong?
39. 39.⚖️ Two fruit sorter models were tested on the same 50 fruit photos. Model A got 49 right and Model B got 46 right. How many percentage points more accurate is Model A?
40. 40.🎯 Meera’s spam spotter is 80% accurate. If it is tested on 100 new messages, how many should it get right?

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