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AI for students lesson 23: Design a tiny AI project · Set 300 · 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.📦 Ishaan collected 70 labelled bird songs for a bird-song app and keeps one fifth of them for testing. How many are left for training?
  2. 2.📋 Planning an AI project: which comes first — work out the accuracy or correct bad labels? (a) work out the accuracy (b) correct bad labels
  3. 3.🧪 Why must you test a model on examples it has NOT seen? (a) to make it bigger (b) to see if it learned (c) to save paper (d) to make it faster
  4. 4.📋 Planning an AI project: which comes first — try unseen examples or calculate percent right? (a) try unseen examples (b) calculate percent right
  5. 5.📋 Planning an AI project: which comes first — choose what to sort or let it learn patterns? (a) choose what to sort (b) let it learn patterns
  6. 6.🧪 What is accuracy? (a) total × 2 (b) total − correct (c) correct ÷ total × 100 (d) correct + total
  7. 7.📦 Kabir collected 40 labelled fruit photos for a fruit sorter and keeps one fifth of them for testing. How many are left for training?
  8. 8.🎯 Tara’s spam spotter was tested on 4 new messages and got 2 right. What is its accuracy in percent?
  9. 9.❌ Nisha’s handwriting reader was tested on 42 new handwritten letters and got 41 right. How many did it get wrong?
  10. 10.⚖️ Two leaf identifier models were tested on the same 20 leaf photos. Model A got 20 right and Model B got 10 right. How many percentage points more accurate is Model A?
  11. 11.📋 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
  12. 12.❌ Saanvi’s recycling sorter was tested on 44 new waste photos and got 40 right. How many did it get wrong?
  13. 13.🎯 Meera’s recycling sorter was tested on 25 new waste photos and got 21 right. What is its accuracy in percent?
  14. 14.⚖️ Two handwriting reader models were tested on the same 50 handwritten letters. Model A got 39 right and Model B got 31 right. How many percentage points more accurate is Model A?
  15. 15.🧪 Your fruit sorter mixes up oranges and lemons. What helps most? (a) more labelled examples (b) fewer examples (c) a new colour screen (d) a louder speaker
  16. 16.📋 Planning an AI project: which comes first — train the model or work out the accuracy? (a) train the model (b) work out the accuracy
  17. 17.❌ Ishaan’s fruit sorter was tested on 34 new fruit photos and got 25 right. How many did it get wrong?
  18. 18.❌ Arjun’s spam spotter was tested on 20 new messages and got 13 right. How many did it get wrong?
  19. 19.🎯 Rohan’s handwriting reader was tested on 25 new handwritten letters and got 13 right. What is its accuracy in percent?
  20. 20.📦 Meera collected 140 labelled fruit photos for a fruit sorter and keeps one fifth of them for testing. How many are left for training?
  21. 21.❌ Saanvi’s fruit sorter was tested on 26 new fruit photos and got 18 right. How many did it get wrong?
  22. 22.📦 Saanvi collected 70 labelled leaf photos for a leaf identifier and keeps one fifth of them for testing. How many are left for training?
  23. 23.🎯 Meera’s bird-song app was tested on 20 new bird songs and got 20 right. What is its accuracy in percent?
  24. 24.📦 Aarav collected 150 labelled handwritten letters for a handwriting reader and keeps one fifth of them for testing. How many are left for training?
  25. 25.🎯 Diya’s handwriting reader was tested on 50 new handwritten letters and got 29 right. What is its accuracy in percent?
  26. 26.📋 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
  27. 27.❌ Ananya’s spam spotter was tested on 17 new messages and got 16 right. How many did it get wrong?
  28. 28.❌ Tara’s bird-song app was tested on 20 new bird songs and got 19 right. How many did it get wrong?
  29. 29.📦 Rohan collected 200 labelled handwritten letters for a handwriting reader and keeps one fifth of them for testing. How many are left for training?
  30. 30.🧪 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
  31. 31.📋 Planning an AI project: which comes first — let it learn patterns or correct bad labels? (a) let it learn patterns (b) correct bad labels
  32. 32.📋 Planning an AI project: which comes first — pick a question to solve or improve data, retest? (a) pick a question to solve (b) improve data, retest
  33. 33.📋 Planning an AI project: which comes first — work out the accuracy or fix it and test again? (a) work out the accuracy (b) fix it and test again
  34. 34.📋 Planning an AI project: which comes first — improve data, retest or calculate percent right? (a) improve data, retest (b) calculate percent right
  35. 35.📋 Planning an AI project: which comes first — let it learn patterns or tag each photo by type? (a) let it learn patterns (b) tag each photo by type
  36. 36.❌ Arjun’s spam spotter was tested on 15 new messages and got 13 right. How many did it get wrong?
  37. 37.📋 Planning an AI project: which comes first — tag each photo by type or recheck every label? (a) tag each photo by type (b) recheck every label
  38. 38.📦 Aarav collected 150 labelled fruit photos for a fruit sorter and keeps one fifth of them for testing. How many are left for training?
  39. 39.📋 Planning an AI project: which comes first — test on new photos or recheck every label? (a) test on new photos (b) recheck every label
  40. 40.🎯 Vihaan’s bird-song app is 60% accurate. If it is tested on 10 new bird songs, how many should it get right?

Answer key

  1. 56
  2. correct bad labels
  3. to see if it learned
  4. try unseen examples
  5. choose what to sort
  6. correct ÷ total × 100
  7. 32
  8. 50
  9. 1
  10. 50
  11. train the model
  12. 4
  13. 84
  14. 16
  15. more labelled examples
  16. train the model
  17. 9
  18. 7
  19. 52
  20. 112
  21. 8
  22. 56
  23. 100
  24. 120
  25. 58
  26. pick a question to solve
  27. 1
  28. 1
  29. 160
  30. paper and examples
  31. correct bad labels
  32. pick a question to solve
  33. work out the accuracy
  34. calculate percent right
  35. tag each photo by type
  36. 2
  37. tag each photo by type
  38. 120
  39. recheck every label
  40. 6

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