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AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 138 · 40 questions
TalentJR

AI tip (Data → model → prediction): Training data = the examples (500 labelled leaf photos, old emails marked spam). The model = the learned patterns that training builds. A prediction = the model’s answer about something NEW (naming a new leaf, flagging a new email). The order is always data → model → prediction.

NameDateTime takenScore ___ / 40
  1. 1.⏩ In machine learning, which comes first: labelled fruit photos or what training builds? (a) labelled fruit photos (b) what training builds
  2. 2.Which of these is a prediction? (a) the learned patterns (b) 500 labelled leaf photos (c) naming a new leaf (d) what training builds
  3. 3.⏩ In machine learning, which comes first: past weather records or the trained program? (a) past weather records (b) the trained program
  4. 4.🔮 A trained model sees a new photo and says “mango”. This is… (a) a password (b) training data (c) a label error (d) a prediction
  5. 5.🔁 Training data, the model or a prediction: “the learned patterns”? (a) the model (b) a prediction (c) training data
  6. 6.⏩ In machine learning, which comes first: past weather records or naming a new fruit photo? (a) past weather records (b) naming a new fruit photo
  7. 7.True or false: “the trained program” is the model. (a) False (b) True
  8. 8.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) a prediction (b) the model (c) training data
  9. 9.True or false: “the trained program” is a prediction. (a) True (b) False
  10. 10.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) the model (b) a prediction (c) training data
  11. 11.Which of these is training data? (a) naming a new fruit photo (b) the learned patterns (c) the trained program (d) labelled fruit photos
  12. 12.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) the model (b) a prediction (c) training data
  13. 13.🔁 Training data, the model or a prediction: “flagging a new email”? (a) training data (b) a prediction (c) the model
  14. 14.🔁 Training data, the model or a prediction: “past weather records”? (a) the model (b) a prediction (c) training data
  15. 15.Which of these is the model? (a) flagging a new email (b) naming a new leaf (c) naming a new fruit photo (d) the trained program
  16. 16.⏩ In machine learning, which comes first: the trained program or recorded spoken words? (a) the trained program (b) recorded spoken words
  17. 17.🔁 Training data, the model or a prediction: “the trained program”? (a) the model (b) a prediction (c) training data
  18. 18.Which of these is a prediction? (a) the learned patterns (b) flagging a new email (c) the trained program (d) 500 labelled leaf photos
  19. 19.True or false: “past weather records” is training data. (a) False (b) True
  20. 20.⏩ In machine learning, which comes first: tomorrow’s rain guess or 500 labelled leaf photos? (a) tomorrow’s rain guess (b) 500 labelled leaf photos
  21. 21.Which of these is the model? (a) old emails marked spam (b) typing a new spoken word (c) naming a new fruit photo (d) the learned patterns
  22. 22.🔁 What is the right order? (a) data, model, prediction (b) prediction, data, model (c) data, prediction, model (d) model, prediction, data
  23. 23.True or false: “500 labelled leaf photos” is training data. (a) False (b) True
  24. 24.🔁 Training data, the model or a prediction: “tomorrow’s rain guess”? (a) training data (b) the model (c) a prediction
  25. 25.🔁 Training data, the model or a prediction: “naming a new leaf”? (a) the model (b) a prediction (c) training data
  26. 26.Which of these is the model? (a) tomorrow’s rain guess (b) flagging a new email (c) old emails marked spam (d) what training builds
  27. 27.True or false: “old emails marked spam” is training data. (a) False (b) True
  28. 28.📦 What happens during training? (a) it prints labels (b) it takes photos (c) it charges up (d) it learns patterns
  29. 29.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) a prediction (b) the model (c) training data
  30. 30.Which of these is a prediction? (a) labelled fruit photos (b) tomorrow’s rain guess (c) the learned patterns (d) past weather records
  31. 31.True or false: “tomorrow’s rain guess” is the model. (a) False (b) True
  32. 32.Which of these is training data? (a) the trained program (b) what training builds (c) naming a new fruit photo (d) past weather records
  33. 33.True or false: “500 labelled leaf photos” is a prediction. (a) True (b) False
  34. 34.⏩ In machine learning, which comes first: what training builds or tomorrow’s rain guess? (a) what training builds (b) tomorrow’s rain guess
  35. 35.Which of these is training data? (a) tomorrow’s rain guess (b) typing a new spoken word (c) old emails marked spam (d) naming a new leaf
  36. 36.⏩ In machine learning, which comes first: what training builds or naming a new leaf? (a) what training builds (b) naming a new leaf
  37. 37.⏩ In machine learning, which comes first: what training builds or past weather records? (a) what training builds (b) past weather records
  38. 38.Which of these is training data? (a) tomorrow’s rain guess (b) typing a new spoken word (c) what training builds (d) recorded spoken words
  39. 39.True or false: “the learned patterns” is the model. (a) True (b) False
  40. 40.True or false: “old emails marked spam” is the model. (a) True (b) False

Answer key

  1. labelled fruit photos
  2. naming a new leaf
  3. past weather records
  4. a prediction
  5. the model
  6. past weather records
  7. True
  8. a prediction
  9. False
  10. training data
  11. labelled fruit photos
  12. training data
  13. a prediction
  14. training data
  15. the trained program
  16. recorded spoken words
  17. the model
  18. flagging a new email
  19. True
  20. 500 labelled leaf photos
  21. the learned patterns
  22. data, model, prediction
  23. True
  24. a prediction
  25. a prediction
  26. what training builds
  27. True
  28. it learns patterns
  29. training data
  30. tomorrow’s rain guess
  31. False
  32. past weather records
  33. False
  34. what training builds
  35. old emails marked spam
  36. what training builds
  37. past weather records
  38. recorded spoken words
  39. True
  40. False

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