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AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 837 · 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.🔁 Training data, the model or a prediction: “naming a new fruit photo”? (a) training data (b) a prediction (c) the model
  2. 2.True or false: “recorded spoken words” is a prediction. (a) True (b) False
  3. 3.📦 What happens during training? (a) it takes photos (b) it prints labels (c) it charges up (d) it learns patterns
  4. 4.Which of these is a prediction? (a) what training builds (b) labelled fruit photos (c) typing a new spoken word (d) the learned patterns
  5. 5.⏩ In machine learning, which comes first: the trained program or flagging a new email? (a) the trained program (b) flagging a new email
  6. 6.True or false: “typing a new spoken word” is a prediction. (a) False (b) True
  7. 7.🔁 What is the right order? (a) data, prediction, model (b) model, prediction, data (c) data, model, prediction (d) prediction, data, model
  8. 8.⏩ In machine learning, which comes first: naming a new fruit photo or the learned patterns? (a) naming a new fruit photo (b) the learned patterns
  9. 9.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) a prediction (b) the model (c) training data
  10. 10.🔮 A trained model sees a new photo and says “mango”. This is… (a) a label error (b) a prediction (c) a password (d) training data
  11. 11.🔁 Training data, the model or a prediction: “tomorrow’s rain guess”? (a) training data (b) a prediction (c) the model
  12. 12.Which of these is the model? (a) naming a new leaf (b) what training builds (c) flagging a new email (d) past weather records
  13. 13.🔁 Training data, the model or a prediction: “the learned patterns”? (a) training data (b) a prediction (c) the model
  14. 14.🔁 Training data, the model or a prediction: “past weather records”? (a) a prediction (b) the model (c) training data
  15. 15.True or false: “500 labelled leaf photos” is the model. (a) True (b) False
  16. 16.True or false: “tomorrow’s rain guess” is a prediction. (a) True (b) False
  17. 17.Which of these is a prediction? (a) past weather records (b) flagging a new email (c) 500 labelled leaf photos (d) what training builds
  18. 18.⏩ In machine learning, which comes first: old emails marked spam or what training builds? (a) old emails marked spam (b) what training builds
  19. 19.Which of these is training data? (a) flagging a new email (b) tomorrow’s rain guess (c) naming a new fruit photo (d) old emails marked spam
  20. 20.Which of these is training data? (a) flagging a new email (b) typing a new spoken word (c) past weather records (d) the trained program
  21. 21.True or false: “flagging a new email” is the model. (a) True (b) False
  22. 22.Which of these is the model? (a) naming a new leaf (b) old emails marked spam (c) tomorrow’s rain guess (d) the trained program
  23. 23.⏩ In machine learning, which comes first: tomorrow’s rain guess or what training builds? (a) tomorrow’s rain guess (b) what training builds
  24. 24.True or false: “flagging a new email” is a prediction. (a) False (b) True
  25. 25.⏩ In machine learning, which comes first: typing a new spoken word or 500 labelled leaf photos? (a) typing a new spoken word (b) 500 labelled leaf photos
  26. 26.Which of these is a prediction? (a) 500 labelled leaf photos (b) tomorrow’s rain guess (c) the learned patterns (d) old emails marked spam
  27. 27.True or false: “the trained program” is training data. (a) False (b) True
  28. 28.Which of these is the model? (a) 500 labelled leaf photos (b) the learned patterns (c) naming a new fruit photo (d) labelled fruit photos
  29. 29.⏩ In machine learning, which comes first: the learned patterns or flagging a new email? (a) the learned patterns (b) flagging a new email
  30. 30.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) training data (b) the model (c) a prediction
  31. 31.🔁 Training data, the model or a prediction: “flagging a new email”? (a) a prediction (b) the model (c) training data
  32. 32.⏩ In machine learning, which comes first: tomorrow’s rain guess or old emails marked spam? (a) tomorrow’s rain guess (b) old emails marked spam
  33. 33.Which of these is a prediction? (a) old emails marked spam (b) labelled fruit photos (c) recorded spoken words (d) naming a new fruit photo
  34. 34.🔁 Training data, the model or a prediction: “the trained program”? (a) the model (b) a prediction (c) training data
  35. 35.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) the model (b) training data (c) a prediction
  36. 36.⏩ In machine learning, which comes first: the learned patterns or old emails marked spam? (a) the learned patterns (b) old emails marked spam
  37. 37.True or false: “labelled fruit photos” is a prediction. (a) False (b) True
  38. 38.True or false: “the trained program” is the model. (a) True (b) False
  39. 39.True or false: “naming a new fruit photo” is the model. (a) False (b) True
  40. 40.⏩ In machine learning, which comes first: the trained program or recorded spoken words? (a) the trained program (b) recorded spoken words

Answer key

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

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