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AI for students lesson 23: Design a tiny AI project · Set 372 · 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.📋 Planning an AI project: which comes first — recheck every label or fix it and test again? (a) recheck every label (b) fix it and test again
  2. 2.📋 Planning an AI project: which comes first — gather many examples or set aside test photos? (a) gather many examples (b) set aside test photos
  3. 3.❌ Vihaan’s handwriting reader was tested on 19 new handwritten letters and got 13 right. How many did it get wrong?
  4. 4.📋 Planning an AI project: which comes first — work out the accuracy or improve data, retest? (a) work out the accuracy (b) improve data, retest
  5. 5.📋 Planning an AI project: which comes first — let it learn patterns or pick a question to solve? (a) let it learn patterns (b) pick a question to solve
  6. 6.📋 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
  7. 7.🧪 Your fruit sorter mixes up oranges and lemons. What helps most? (a) more labelled examples (b) a new colour screen (c) fewer examples (d) a louder speaker
  8. 8.🎯 Vihaan’s recycling sorter was tested on 4 new waste photos and got 3 right. What is its accuracy in percent?
  9. 9.📋 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
  10. 10.📋 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
  11. 11.📋 Planning an AI project: which comes first — choose what to sort or label each example? (a) choose what to sort (b) label each example
  12. 12.📦 Kabir collected 50 labelled handwritten letters for a handwriting reader and keeps one fifth of them for testing. How many are left for training?
  13. 13.📋 Planning an AI project: which comes first — recheck every label or pick a question to solve? (a) recheck every label (b) pick a question to solve
  14. 14.📋 Planning an AI project: which comes first — collect fruit photos or recheck every label? (a) collect fruit photos (b) recheck every label
  15. 15.📋 Planning an AI project: which comes first — try unseen examples or calculate percent right? (a) try unseen examples (b) calculate percent right
  16. 16.❌ Aarav’s spam spotter was tested on 17 new messages and got 15 right. How many did it get wrong?
  17. 17.🎯 Tara’s spam spotter was tested on 25 new messages and got 25 right. What is its accuracy in percent?
  18. 18.🎯 Meera’s recycling sorter was tested on 10 new waste photos and got 5 right. What is its accuracy in percent?
  19. 19.📋 Planning an AI project: which comes first — correct bad labels or pick a question to solve? (a) correct bad labels (b) pick a question to solve
  20. 20.🧪 You can plan a simple AI project with… (a) nothing at all (b) paper and examples (c) only a big robot (d) a secret password
  21. 21.❌ Meera’s bird-song app was tested on 23 new bird songs and got 16 right. How many did it get wrong?
  22. 22.📋 Planning an AI project: which comes first — gather many examples or calculate percent right? (a) gather many examples (b) calculate percent right
  23. 23.🎯 Kabir’s spam spotter was tested on 4 new messages and got 4 right. What is its accuracy in percent?
  24. 24.📋 Planning an AI project: which comes first — set aside test photos or train the model? (a) set aside test photos (b) train the model
  25. 25.❌ Ishaan’s fruit sorter was tested on 21 new fruit photos and got 15 right. How many did it get wrong?
  26. 26.❌ Tara’s handwriting reader was tested on 39 new handwritten letters and got 33 right. How many did it get wrong?
  27. 27.📦 Ishaan collected 70 labelled leaf photos for a leaf identifier and keeps one fifth of them for testing. How many are left for training?
  28. 28.📋 Planning an AI project: which comes first — pick a question to solve or test on new photos? (a) pick a question to solve (b) test on new photos
  29. 29.🎯 Rohan’s fruit sorter is 50% accurate. If it is tested on 10 new fruit photos, how many should it get right?
  30. 30.🎯 Aarav’s spam spotter was tested on 20 new messages and got 20 right. What is its accuracy in percent?
  31. 31.🎯 Meera’s recycling sorter was tested on 5 new waste photos and got 3 right. What is its accuracy in percent?
  32. 32.📋 Planning an AI project: which comes first — try unseen examples or improve data, retest? (a) try unseen examples (b) improve data, retest
  33. 33.🎯 Rohan’s recycling sorter is 60% accurate. If it is tested on 100 new waste photos, how many should it get right?
  34. 34.📋 Planning an AI project: which comes first — calculate percent right or fix it and test again? (a) calculate percent right (b) fix it and test again
  35. 35.❌ Ishaan’s bird-song app was tested on 45 new bird songs and got 41 right. How many did it get wrong?
  36. 36.⚖️ Two fruit sorter models were tested on the same 50 fruit photos. Model A got 38 right and Model B got 30 right. How many percentage points more accurate is Model A?
  37. 37.🎯 Saanvi’s fruit sorter is 50% accurate. If it is tested on 60 new fruit photos, how many should it get right?
  38. 38.🧪 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
  39. 39.❌ Ishaan’s recycling sorter was tested on 25 new waste photos and got 22 right. How many did it get wrong?
  40. 40.❌ Meera’s recycling sorter was tested on 20 new waste photos and got 18 right. How many did it get wrong?

Answer key

  1. recheck every label
  2. gather many examples
  3. 6
  4. work out the accuracy
  5. pick a question to solve
  6. calculate percent right
  7. more labelled examples
  8. 75
  9. train the model
  10. set aside test photos
  11. choose what to sort
  12. 40
  13. pick a question to solve
  14. collect fruit photos
  15. try unseen examples
  16. 2
  17. 100
  18. 50
  19. pick a question to solve
  20. paper and examples
  21. 7
  22. gather many examples
  23. 100
  24. set aside test photos
  25. 6
  26. 6
  27. 56
  28. pick a question to solve
  29. 5
  30. 100
  31. 60
  32. try unseen examples
  33. 60
  34. calculate percent right
  35. 4
  36. 16
  37. 30
  38. to see if it learned
  39. 3
  40. 2

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