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AI for students lesson 23: Design a tiny AI project · Set 769 · 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.🎯 Kabir’s spam spotter was tested on 4 new messages and got 2 right. What is its accuracy in percent?
  2. 2.🧪 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
  3. 3.❌ Vihaan’s handwriting reader was tested on 49 new handwritten letters and got 42 right. How many did it get wrong?
  4. 4.🎯 Rohan’s spam spotter was tested on 50 new messages and got 38 right. What is its accuracy in percent?
  5. 5.📋 Planning an AI project: which comes first — let it learn patterns or set aside test photos? (a) let it learn patterns (b) set aside test photos
  6. 6.🎯 Meera’s handwriting reader was tested on 50 new handwritten letters and got 27 right. What is its accuracy in percent?
  7. 7.📦 Ananya collected 90 labelled fruit photos for a fruit sorter and keeps one fifth of them for testing. How many are left for training?
  8. 8.❌ Aarav’s fruit sorter was tested on 20 new fruit photos and got 15 right. How many did it get wrong?
  9. 9.📋 Planning an AI project: which comes first — train the model or test on new photos? (a) train the model (b) test on new photos
  10. 10.⚖️ Two bird-song app models were tested on the same 50 bird songs. Model A got 32 right and Model B got 29 right. How many percentage points more accurate is Model A?
  11. 11.❌ Ishaan’s bird-song app was tested on 33 new bird songs and got 24 right. How many did it get wrong?
  12. 12.📋 Planning an AI project: which comes first — correct bad labels or fix it and test again? (a) correct bad labels (b) fix it and test again
  13. 13.📋 Planning an AI project: which comes first — train the model or split train and test? (a) train the model (b) split train and test
  14. 14.📋 Planning an AI project: which comes first — let it learn patterns or collect fruit photos? (a) let it learn patterns (b) collect fruit photos
  15. 15.📦 Tara collected 40 labelled messages for a spam spotter and keeps one fifth of them for testing. How many are left for training?
  16. 16.📦 Nisha collected 120 labelled leaf photos for a leaf identifier and keeps one fifth of them for testing. How many are left for training?
  17. 17.📦 Diya collected 110 labelled waste photos for a recycling sorter and keeps one fifth of them for testing. How many are left for training?
  18. 18.📦 Ananya collected 80 labelled messages for a spam spotter and keeps one fifth of them for testing. How many are left for training?
  19. 19.❌ Ananya’s fruit sorter was tested on 23 new fruit photos and got 19 right. How many did it get wrong?
  20. 20.❌ Ishaan’s handwriting reader was tested on 24 new handwritten letters and got 18 right. How many did it get wrong?
  21. 21.🧪 Your fruit sorter mixes up oranges and lemons. What helps most? (a) fewer examples (b) more labelled examples (c) a louder speaker (d) a new colour screen
  22. 22.🧪 What is accuracy? (a) total − correct (b) correct + total (c) correct ÷ total × 100 (d) total × 2
  23. 23.🎯 Diya’s handwriting reader is 90% accurate. If it is tested on 80 new handwritten letters, how many should it get right?
  24. 24.🎯 Diya’s leaf identifier was tested on 4 new leaf photos and got 3 right. What is its accuracy in percent?
  25. 25.📦 Rohan collected 120 labelled handwritten letters for a handwriting reader and keeps one fifth of them for testing. How many are left for training?
  26. 26.🧪 You can plan a simple AI project with… (a) paper and examples (b) a secret password (c) nothing at all (d) only a big robot
  27. 27.🎯 Saanvi’s recycling sorter was tested on 25 new waste photos and got 18 right. What is its accuracy in percent?
  28. 28.❌ Meera’s handwriting reader was tested on 14 new handwritten letters and got 10 right. How many did it get wrong?
  29. 29.🎯 Ishaan’s fruit sorter is 70% accurate. If it is tested on 20 new fruit photos, how many should it get right?
  30. 30.❌ Saanvi’s spam spotter was tested on 34 new messages and got 29 right. How many did it get wrong?
  31. 31.📋 Planning an AI project: which comes first — tag each photo by type or calculate percent right? (a) tag each photo by type (b) calculate percent right
  32. 32.🎯 Aarav’s spam spotter was tested on 4 new messages and got 4 right. What is its accuracy in percent?
  33. 33.🎯 Diya’s recycling sorter is 60% accurate. If it is tested on 10 new waste photos, how many should it get right?
  34. 34.⚖️ Two recycling sorter models were tested on the same 10 waste photos. Model A got 9 right and Model B got 8 right. How many percentage points more accurate is Model A?
  35. 35.📋 Planning an AI project: which comes first — split train and test or recheck every label? (a) split train and test (b) recheck every label
  36. 36.❌ Saanvi’s handwriting reader was tested on 39 new handwritten letters and got 35 right. How many did it get wrong?
  37. 37.📦 Aarav collected 180 labelled handwritten letters for a handwriting reader and keeps one fifth of them for testing. How many are left for training?
  38. 38.📋 Planning an AI project: which comes first — test on new photos or improve data, retest? (a) test on new photos (b) improve data, retest
  39. 39.📋 Planning an AI project: which comes first — fix it and test again or calculate percent right? (a) fix it and test again (b) calculate percent right
  40. 40.📋 Planning an AI project: which comes first — test on new photos or fix it and test again? (a) test on new photos (b) fix it and test again

Answer key

  1. 50
  2. to see if it learned
  3. 7
  4. 76
  5. set aside test photos
  6. 54
  7. 72
  8. 5
  9. train the model
  10. 6
  11. 9
  12. correct bad labels
  13. split train and test
  14. collect fruit photos
  15. 32
  16. 96
  17. 88
  18. 64
  19. 4
  20. 6
  21. more labelled examples
  22. correct ÷ total × 100
  23. 72
  24. 75
  25. 96
  26. paper and examples
  27. 72
  28. 4
  29. 14
  30. 5
  31. tag each photo by type
  32. 100
  33. 6
  34. 10
  35. recheck every label
  36. 4
  37. 144
  38. test on new photos
  39. calculate percent right
  40. test on new photos

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