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AI for students lesson 23: Design a tiny AI project · Set 516 · 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 — train the model or try unseen examples? (a) train the model (b) try unseen examples
  2. 2.⚖️ Two bird-song app models were tested on the same 10 bird songs. Model A got 7 right and Model B got 6 right. How many percentage points more accurate is Model A?
  3. 3.📋 Planning an AI project: which comes first — try unseen examples or recheck every label? (a) try unseen examples (b) recheck every label
  4. 4.📋 Planning an AI project: which comes first — set aside test photos or label each example? (a) set aside test photos (b) label each example
  5. 5.⚖️ Two fruit sorter models were tested on the same 20 fruit photos. Model A got 14 right and Model B got 10 right. How many percentage points more accurate is Model A?
  6. 6.❌ Diya’s handwriting reader was tested on 46 new handwritten letters and got 43 right. How many did it get wrong?
  7. 7.❌ Ishaan’s recycling sorter was tested on 50 new waste photos and got 41 right. How many did it get wrong?
  8. 8.🎯 Nisha’s fruit sorter is 60% accurate. If it is tested on 70 new fruit photos, how many should it get right?
  9. 9.🧪 What is accuracy? (a) correct ÷ total × 100 (b) correct + total (c) total − correct (d) total × 2
  10. 10.📋 Planning an AI project: which comes first — correct bad labels or label each example? (a) correct bad labels (b) label each example
  11. 11.🧪 Your fruit sorter mixes up oranges and lemons. What helps most? (a) a new colour screen (b) more labelled examples (c) fewer examples (d) a louder speaker
  12. 12.🎯 Rohan’s fruit sorter was tested on 25 new fruit photos and got 20 right. What is its accuracy in percent?
  13. 13.🧪 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
  14. 14.🎯 Vihaan’s bird-song app is 50% accurate. If it is tested on 40 new bird songs, how many should it get right?
  15. 15.🧪 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
  16. 16.📋 Planning an AI project: which comes first — try unseen examples or calculate percent right? (a) try unseen examples (b) calculate percent right
  17. 17.📋 Planning an AI project: which comes first — train the model or set aside test photos? (a) train the model (b) set aside test photos
  18. 18.📦 Tara collected 40 labelled fruit photos for a fruit sorter and keeps one fifth of them for testing. How many are left for training?
  19. 19.📋 Planning an AI project: which comes first — correct bad labels or try unseen examples? (a) correct bad labels (b) try unseen examples
  20. 20.⚖️ Two recycling sorter models were tested on the same 20 waste photos. Model A got 19 right and Model B got 13 right. How many percentage points more accurate is Model A?
  21. 21.⚖️ Two bird-song app models were tested on the same 20 bird songs. Model A got 18 right and Model B got 15 right. How many percentage points more accurate is Model A?
  22. 22.⚖️ Two recycling sorter models were tested on the same 25 waste photos. Model A got 24 right and Model B got 21 right. How many percentage points more accurate is Model A?
  23. 23.🎯 Saanvi’s handwriting reader was tested on 25 new handwritten letters and got 16 right. What is its accuracy in percent?
  24. 24.🎯 Arjun’s handwriting reader was tested on 50 new handwritten letters and got 27 right. What is its accuracy in percent?
  25. 25.🎯 Arjun’s fruit sorter was tested on 5 new fruit photos and got 5 right. What is its accuracy in percent?
  26. 26.🎯 Diya’s handwriting reader is 50% accurate. If it is tested on 60 new handwritten letters, how many should it get right?
  27. 27.📋 Planning an AI project: which comes first — let it learn patterns or test on new photos? (a) let it learn patterns (b) test on new photos
  28. 28.🎯 Diya’s leaf identifier is 80% accurate. If it is tested on 90 new leaf photos, how many should it get right?
  29. 29.📦 Nisha collected 40 labelled handwritten letters for a handwriting reader and keeps one fifth of them for testing. How many are left for training?
  30. 30.🎯 Ishaan’s recycling sorter was tested on 25 new waste photos and got 19 right. What is its accuracy in percent?
  31. 31.📋 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
  32. 32.📦 Ananya collected 110 labelled fruit photos for a fruit sorter and keeps one fifth of them for testing. How many are left for training?
  33. 33.🎯 Saanvi’s fruit sorter is 80% accurate. If it is tested on 20 new fruit photos, how many should it get right?
  34. 34.📋 Planning an AI project: which comes first — work out the accuracy or tag each photo by type? (a) work out the accuracy (b) tag each photo by type
  35. 35.🎯 Aarav’s spam spotter is 80% accurate. If it is tested on 10 new messages, how many should it get right?
  36. 36.📋 Planning an AI project: which comes first — work out the accuracy or try unseen examples? (a) work out the accuracy (b) try unseen examples
  37. 37.🎯 Kabir’s recycling sorter was tested on 4 new waste photos and got 2 right. What is its accuracy in percent?
  38. 38.📋 Planning an AI project: which comes first — train the model or improve data, retest? (a) train the model (b) improve data, retest
  39. 39.⚖️ Two fruit sorter models were tested on the same 20 fruit photos. Model A got 17 right and Model B got 12 right. How many percentage points more accurate is Model A?
  40. 40.📋 Planning an AI project: which comes first — try unseen examples or pick a question to solve? (a) try unseen examples (b) pick a question to solve

Answer key

  1. train the model
  2. 10
  3. recheck every label
  4. label each example
  5. 20
  6. 3
  7. 9
  8. 42
  9. correct ÷ total × 100
  10. label each example
  11. more labelled examples
  12. 80
  13. paper and examples
  14. 20
  15. to see if it learned
  16. try unseen examples
  17. set aside test photos
  18. 32
  19. correct bad labels
  20. 30
  21. 15
  22. 12
  23. 64
  24. 54
  25. 100
  26. 30
  27. let it learn patterns
  28. 72
  29. 32
  30. 76
  31. tag each photo by type
  32. 88
  33. 16
  34. tag each photo by type
  35. 8
  36. try unseen examples
  37. 50
  38. train the model
  39. 25
  40. pick a question to solve

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