Build Your Own AI Project Worksheet

AI for students lesson 23: Design a tiny AI project · Set 969 · 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.🎯 Meera’s handwriting reader is 70% accurate. If it is tested on 70 new handwritten letters, how many should it get right?
2. 2.⚖️ Two leaf identifier models were tested on the same 10 leaf photos. Model A got 9 right and Model B got 5 right. How many percentage points more accurate is Model A?
3. 3.⚖️ Two leaf identifier models were tested on the same 10 leaf photos. Model A got 6 right and Model B got 5 right. How many percentage points more accurate is Model A?
4. 4.🧪 What is accuracy? (a) total × 2 (b) correct ÷ total × 100 (c) correct + total (d) total − correct
5. 5.🎯 Kabir’s leaf identifier is 50% accurate. If it is tested on 60 new leaf photos, how many should it get right?
6. 6.📋 Planning an AI project: which comes first — improve data, retest or work out the accuracy? (a) improve data, retest (b) work out the accuracy
7. 7.🎯 Arjun’s recycling sorter was tested on 50 new waste photos and got 40 right. What is its accuracy in percent?
8. 8.📦 Diya collected 150 labelled handwritten letters for a handwriting reader and keeps one fifth of them for testing. How many are left for training?
9. 9.🎯 Nisha’s leaf identifier was tested on 20 new leaf photos and got 12 right. What is its accuracy in percent?
10. 10.📋 Planning an AI project: which comes first — pick a question to solve or work out the accuracy? (a) pick a question to solve (b) work out the accuracy
11. 11.🎯 Diya’s fruit sorter was tested on 4 new fruit photos and got 3 right. What is its accuracy in percent?
12. 12.❌ Rohan’s leaf identifier was tested on 40 new leaf photos and got 36 right. How many did it get wrong?
13. 13.🧪 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
14. 14.❌ Diya’s leaf identifier was tested on 24 new leaf photos and got 18 right. How many did it get wrong?
15. 15.🧪 Why must you test a model on examples it has NOT seen? (a) to see if it learned (b) to make it faster (c) to save paper (d) to make it bigger
16. 16.📋 Planning an AI project: which comes first — improve data, retest or set aside test photos? (a) improve data, retest (b) set aside test photos
17. 17.⚖️ Two spam spotter models were tested on the same 50 messages. Model A got 47 right and Model B got 45 right. How many percentage points more accurate is Model A?
18. 18.📦 Rohan collected 110 labelled messages for a spam spotter and keeps one fifth of them for testing. How many are left for training?
19. 19.❌ Kabir’s leaf identifier was tested on 31 new leaf photos and got 26 right. How many did it get wrong?
20. 20.📋 Planning an AI project: which comes first — improve data, retest or calculate percent right? (a) improve data, retest (b) calculate percent right
21. 21.📋 Planning an AI project: which comes first — gather many examples or correct bad labels? (a) gather many examples (b) correct bad labels
22. 22.⚖️ Two handwriting reader models were tested on the same 25 handwritten letters. Model A got 18 right and Model B got 17 right. How many percentage points more accurate is Model A?
23. 23.🎯 Aarav’s leaf identifier is 70% accurate. If it is tested on 30 new leaf photos, how many should it get right?
24. 24.📋 Planning an AI project: which comes first — let it learn patterns or collect fruit photos? (a) let it learn patterns (b) collect fruit photos
25. 25.⚖️ Two leaf identifier models were tested on the same 20 leaf photos. Model A got 19 right and Model B got 13 right. How many percentage points more accurate is Model A?
26. 26.📋 Planning an AI project: which comes first — collect fruit photos or let it learn patterns? (a) collect fruit photos (b) let it learn patterns
27. 27.🧪 You can plan a simple AI project with… (a) only a big robot (b) nothing at all (c) paper and examples (d) a secret password
28. 28.⚖️ Two fruit sorter models were tested on the same 25 fruit photos. Model A got 18 right and Model B got 17 right. How many percentage points more accurate is Model A?
29. 29.🎯 Aarav’s bird-song app is 60% accurate. If it is tested on 20 new bird songs, how many should it get right?
30. 30.❌ Kabir’s handwriting reader was tested on 37 new handwritten letters and got 34 right. How many did it get wrong?
31. 31.🎯 Ishaan’s fruit sorter was tested on 25 new fruit photos and got 17 right. What is its accuracy in percent?
32. 32.📦 Meera collected 200 labelled waste photos for a recycling sorter and keeps one fifth of them for testing. How many are left for training?
33. 33.⚖️ Two spam spotter models were tested on the same 10 messages. Model A got 6 right and Model B got 5 right. How many percentage points more accurate is Model A?
34. 34.📋 Planning an AI project: which comes first — test on new photos or calculate percent right? (a) test on new photos (b) calculate percent right
35. 35.📋 Planning an AI project: which comes first — test on new photos or label each example? (a) test on new photos (b) label each example
36. 36.🎯 Saanvi’s handwriting reader was tested on 4 new handwritten letters and got 3 right. What is its accuracy in percent?
37. 37.📋 Planning an AI project: which comes first — test on new photos or work out the accuracy? (a) test on new photos (b) work out the accuracy
38. 38.🎯 Rohan’s leaf identifier is 80% accurate. If it is tested on 50 new leaf photos, how many should it get right?
39. 39.❌ Diya’s recycling sorter was tested on 15 new waste photos and got 12 right. How many did it get wrong?
40. 40.📦 Aarav collected 70 labelled bird songs for a bird-song app and keeps one fifth of them for testing. How many are left for training?

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