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AI for students lesson 23: Design a tiny AI project · Set 248 · 40 questions
TalentJR

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.

NameDateTime takenScore ___ / 40
  1. 1.🧪 Your fruit sorter mixes up oranges and lemons. What helps most? (a) a new colour screen (b) a louder speaker (c) more labelled examples (d) fewer examples
  2. 2.🎯 Ishaan’s handwriting reader is 70% accurate. If it is tested on 30 new handwritten letters, how many should it get right?
  3. 3.🧪 Why must you test a model on examples it has NOT seen? (a) to make it bigger (b) to save paper (c) to make it faster (d) to see if it learned
  4. 4.🎯 Ishaan’s recycling sorter is 50% accurate. If it is tested on 40 new waste photos, how many should it get right?
  5. 5.📋 Planning an AI project: which comes first — split train and test or let it learn patterns? (a) split train and test (b) let it learn patterns
  6. 6.❌ Diya’s recycling sorter was tested on 40 new waste photos and got 35 right. How many did it get wrong?
  7. 7.🧪 What is accuracy? (a) total × 2 (b) total − correct (c) correct + total (d) correct ÷ total × 100
  8. 8.❌ Rohan’s leaf identifier was tested on 50 new leaf photos and got 49 right. How many did it get wrong?
  9. 9.🧪 You can plan a simple AI project with… (a) nothing at all (b) only a big robot (c) paper and examples (d) a secret password
  10. 10.🎯 Aarav’s bird-song app was tested on 50 new bird songs and got 28 right. What is its accuracy in percent?
  11. 11.🎯 Aarav’s recycling sorter is 80% accurate. If it is tested on 70 new waste photos, how many should it get right?
  12. 12.📋 Planning an AI project: which comes first — correct bad labels or set aside test photos? (a) correct bad labels (b) set aside test photos
  13. 13.❌ Nisha’s leaf identifier was tested on 49 new leaf photos and got 40 right. How many did it get wrong?
  14. 14.🎯 Ishaan’s handwriting reader was tested on 4 new handwritten letters and got 3 right. What is its accuracy in percent?
  15. 15.📋 Planning an AI project: which comes first — calculate percent right or improve data, retest? (a) calculate percent right (b) improve data, retest
  16. 16.📦 Vihaan collected 130 labelled fruit photos for a fruit sorter and keeps one fifth of them for testing. How many are left for training?
  17. 17.🎯 Aarav’s bird-song app was tested on 5 new bird songs and got 5 right. What is its accuracy in percent?
  18. 18.🎯 Saanvi’s leaf identifier was tested on 4 new leaf photos and got 4 right. What is its accuracy in percent?
  19. 19.📦 Tara collected 190 labelled messages for a spam spotter and keeps one fifth of them for testing. How many are left for training?
  20. 20.📋 Planning an AI project: which comes first — set aside test photos or tag each photo by type? (a) set aside test photos (b) tag each photo by type
  21. 21.❌ Nisha’s recycling sorter was tested on 30 new waste photos and got 23 right. How many did it get wrong?
  22. 22.⚖️ Two fruit sorter models were tested on the same 25 fruit photos. Model A got 21 right and Model B got 15 right. How many percentage points more accurate is Model A?
  23. 23.❌ Rohan’s bird-song app was tested on 40 new bird songs and got 32 right. How many did it get wrong?
  24. 24.📋 Planning an AI project: which comes first — try unseen examples or correct bad labels? (a) try unseen examples (b) correct bad labels
  25. 25.📋 Planning an AI project: which comes first — tag each photo by type or fix it and test again? (a) tag each photo by type (b) fix it and test again
  26. 26.📋 Planning an AI project: which comes first — pick a question to solve or split train and test? (a) pick a question to solve (b) split train and test
  27. 27.⚖️ Two spam spotter models were tested on the same 50 messages. Model A got 38 right and Model B got 33 right. How many percentage points more accurate is Model A?
  28. 28.🎯 Diya’s spam spotter is 60% accurate. If it is tested on 40 new messages, how many should it get right?
  29. 29.📋 Planning an AI project: which comes first — split train and test or try unseen examples? (a) split train and test (b) try unseen examples
  30. 30.❌ Saanvi’s spam spotter was tested on 20 new messages and got 18 right. How many did it get wrong?
  31. 31.📋 Planning an AI project: which comes first — split train and test or calculate percent right? (a) split train and test (b) calculate percent right
  32. 32.🎯 Ananya’s bird-song app is 70% accurate. If it is tested on 20 new bird songs, how many should it get right?
  33. 33.🎯 Vihaan’s handwriting reader was tested on 50 new handwritten letters and got 41 right. What is its accuracy in percent?
  34. 34.⚖️ Two recycling sorter models were tested on the same 10 waste photos. Model A got 10 right and Model B got 9 right. How many percentage points more accurate is Model A?
  35. 35.🎯 Aarav’s fruit sorter was tested on 20 new fruit photos and got 11 right. What is its accuracy in percent?
  36. 36.📋 Planning an AI project: which comes first — let it learn patterns or split train and test? (a) let it learn patterns (b) split train and test
  37. 37.📋 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
  38. 38.🎯 Meera’s bird-song app was tested on 4 new bird songs and got 4 right. What is its accuracy in percent?
  39. 39.📦 Meera collected 170 labelled leaf photos for a leaf identifier and keeps one fifth of them for testing. How many are left for training?
  40. 40.❌ Diya’s spam spotter was tested on 47 new messages and got 41 right. How many did it get wrong?

Answer key

  1. more labelled examples
  2. 21
  3. to see if it learned
  4. 20
  5. split train and test
  6. 5
  7. correct ÷ total × 100
  8. 1
  9. paper and examples
  10. 56
  11. 56
  12. correct bad labels
  13. 9
  14. 75
  15. calculate percent right
  16. 104
  17. 100
  18. 100
  19. 152
  20. tag each photo by type
  21. 7
  22. 24
  23. 8
  24. correct bad labels
  25. tag each photo by type
  26. pick a question to solve
  27. 10
  28. 24
  29. split train and test
  30. 2
  31. split train and test
  32. 14
  33. 82
  34. 10
  35. 55
  36. split train and test
  37. train the model
  38. 100
  39. 136
  40. 6

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