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AI for students lesson 23: Design a tiny AI project · Set 938 · 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.🎯 Nisha’s fruit sorter was tested on 25 new fruit photos and got 19 right. What is its accuracy in percent?
  2. 2.📋 Planning an AI project: which comes first — set aside test photos or work out the accuracy? (a) set aside test photos (b) work out the accuracy
  3. 3.📋 Planning an AI project: which comes first — try unseen examples or correct bad labels? (a) try unseen examples (b) correct bad labels
  4. 4.🧪 Your fruit sorter mixes up oranges and lemons. What helps most? (a) a louder speaker (b) a new colour screen (c) more labelled examples (d) fewer examples
  5. 5.📦 Arjun collected 60 labelled bird songs for a bird-song app and keeps one fifth of them for testing. How many are left for training?
  6. 6.🧪 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 bigger (d) to make it faster
  7. 7.🎯 Arjun’s leaf identifier was tested on 25 new leaf photos and got 19 right. What is its accuracy in percent?
  8. 8.📋 Planning an AI project: which comes first — let it learn patterns or label each example? (a) let it learn patterns (b) label each example
  9. 9.📋 Planning an AI project: which comes first — try unseen examples or recheck every label? (a) try unseen examples (b) recheck every label
  10. 10.🎯 Tara’s handwriting reader is 70% accurate. If it is tested on 60 new handwritten letters, how many should it get right?
  11. 11.❌ Diya’s bird-song app was tested on 14 new bird songs and got 10 right. How many did it get wrong?
  12. 12.📦 Meera collected 40 labelled bird songs for a bird-song app and keeps one fifth of them for testing. How many are left for training?
  13. 13.🎯 Ishaan’s fruit sorter is 60% accurate. If it is tested on 70 new fruit photos, how many should it get right?
  14. 14.📋 Planning an AI project: which comes first — test on new photos or label each example? (a) test on new photos (b) label each example
  15. 15.❌ Meera’s bird-song app was tested on 48 new bird songs and got 39 right. How many did it get wrong?
  16. 16.🎯 Vihaan’s bird-song app is 60% accurate. If it is tested on 10 new bird songs, how many should it get right?
  17. 17.📋 Planning an AI project: which comes first — calculate percent right or improve data, retest? (a) calculate percent right (b) improve data, retest
  18. 18.🎯 Nisha’s bird-song app was tested on 50 new bird songs and got 27 right. What is its accuracy in percent?
  19. 19.🎯 Tara’s leaf identifier was tested on 10 new leaf photos and got 5 right. What is its accuracy in percent?
  20. 20.🎯 Nisha’s recycling sorter is 50% accurate. If it is tested on 50 new waste photos, how many should it get right?
  21. 21.🎯 Ishaan’s leaf identifier is 50% accurate. If it is tested on 30 new leaf photos, how many should it get right?
  22. 22.❌ Vihaan’s leaf identifier was tested on 32 new leaf photos and got 27 right. How many did it get wrong?
  23. 23.📋 Planning an AI project: which comes first — tag each photo by type or gather many examples? (a) tag each photo by type (b) gather many examples
  24. 24.⚖️ Two recycling sorter models were tested on the same 20 waste photos. Model A got 20 right and Model B got 17 right. How many percentage points more accurate is Model A?
  25. 25.⚖️ Two fruit sorter models were tested on the same 25 fruit photos. Model A got 25 right and Model B got 20 right. How many percentage points more accurate is Model A?
  26. 26.🎯 Aarav’s leaf identifier was tested on 5 new leaf photos and got 3 right. What is its accuracy in percent?
  27. 27.🧪 What is accuracy? (a) correct + total (b) total − correct (c) total × 2 (d) correct ÷ total × 100
  28. 28.📋 Planning an AI project: which comes first — collect fruit photos or fix it and test again? (a) collect fruit photos (b) fix it and test again
  29. 29.📋 Planning an AI project: which comes first — train the model or improve data, retest? (a) train the model (b) improve data, retest
  30. 30.📦 Ananya collected 50 labelled leaf photos for a leaf identifier and keeps one fifth of them for testing. How many are left for training?
  31. 31.🎯 Meera’s fruit sorter was tested on 4 new fruit photos and got 2 right. What is its accuracy in percent?
  32. 32.🎯 Arjun’s handwriting reader was tested on 25 new handwritten letters and got 13 right. What is its accuracy in percent?
  33. 33.⚖️ Two handwriting reader models were tested on the same 10 handwritten letters. Model A got 8 right and Model B got 5 right. How many percentage points more accurate is Model A?
  34. 34.⚖️ Two recycling sorter models were tested on the same 10 waste photos. Model A got 10 right and Model B got 5 right. How many percentage points more accurate is Model A?
  35. 35.📋 Planning an AI project: which comes first — collect fruit photos or choose what to sort? (a) collect fruit photos (b) choose what to sort
  36. 36.📦 Rohan 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.🎯 Aarav’s spam spotter was tested on 20 new messages and got 10 right. What is its accuracy in percent?
  38. 38.📋 Planning an AI project: which comes first — test on new photos or train the model? (a) test on new photos (b) train the model
  39. 39.❌ Meera’s spam spotter was tested on 35 new messages and got 32 right. How many did it get wrong?
  40. 40.📋 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

Answer key

  1. 76
  2. set aside test photos
  3. correct bad labels
  4. more labelled examples
  5. 48
  6. to see if it learned
  7. 76
  8. label each example
  9. recheck every label
  10. 42
  11. 4
  12. 32
  13. 42
  14. label each example
  15. 9
  16. 6
  17. calculate percent right
  18. 54
  19. 50
  20. 25
  21. 15
  22. 5
  23. gather many examples
  24. 15
  25. 20
  26. 60
  27. correct ÷ total × 100
  28. collect fruit photos
  29. train the model
  30. 40
  31. 50
  32. 52
  33. 30
  34. 50
  35. choose what to sort
  36. 32
  37. 50
  38. train the model
  39. 3
  40. test on new photos

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