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AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 978 · 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.Which of these is training data? (a) typing a new spoken word (b) flagging a new email (c) 500 labelled leaf photos (d) naming a new fruit photo
  2. 2.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) a prediction (b) training data (c) the model
  3. 3.True or false: “labelled fruit photos” is a prediction. (a) True (b) False
  4. 4.Which of these is training data? (a) old emails marked spam (b) naming a new fruit photo (c) typing a new spoken word (d) what training builds
  5. 5.Which of these is training data? (a) naming a new fruit photo (b) the trained program (c) past weather records (d) the learned patterns
  6. 6.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) training data (b) a prediction (c) the model
  7. 7.🔁 Training data, the model or a prediction: “naming a new leaf”? (a) a prediction (b) training data (c) the model
  8. 8.True or false: “past weather records” is a prediction. (a) False (b) True
  9. 9.True or false: “old emails marked spam” is training data. (a) True (b) False
  10. 10.🧪 Why test a model on NEW examples? (a) to make it slower (b) to change its name (c) to see if it works (d) to delete its data
  11. 11.⏩ In machine learning, which comes first: the learned patterns or labelled fruit photos? (a) the learned patterns (b) labelled fruit photos
  12. 12.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) a prediction (b) the model (c) training data
  13. 13.🔁 Training data, the model or a prediction: “the learned patterns”? (a) a prediction (b) the model (c) training data
  14. 14.🔁 Training data, the model or a prediction: “naming a new fruit photo”? (a) the model (b) a prediction (c) training data
  15. 15.⏩ In machine learning, which comes first: what training builds or naming a new fruit photo? (a) what training builds (b) naming a new fruit photo
  16. 16.True or false: “500 labelled leaf photos” is training data. (a) False (b) True
  17. 17.🔁 Training data, the model or a prediction: “flagging a new email”? (a) training data (b) the model (c) a prediction
  18. 18.📦 What happens during training? (a) it charges up (b) it learns patterns (c) it takes photos (d) it prints labels
  19. 19.True or false: “what training builds” is the model. (a) False (b) True
  20. 20.⏩ In machine learning, which comes first: flagging a new email or what training builds? (a) flagging a new email (b) what training builds
  21. 21.🔮 A trained model sees a new photo and says “mango”. This is… (a) training data (b) a prediction (c) a label error (d) a password
  22. 22.🔁 Training data, the model or a prediction: “what training builds”? (a) the model (b) a prediction (c) training data
  23. 23.⏩ In machine learning, which comes first: the trained program or typing a new spoken word? (a) the trained program (b) typing a new spoken word
  24. 24.True or false: “tomorrow’s rain guess” is a prediction. (a) True (b) False
  25. 25.⏩ In machine learning, which comes first: old emails marked spam or typing a new spoken word? (a) old emails marked spam (b) typing a new spoken word
  26. 26.True or false: “recorded spoken words” is a prediction. (a) False (b) True
  27. 27.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) a prediction (b) the model (c) training data
  28. 28.🔁 What is the right order? (a) prediction, data, model (b) model, prediction, data (c) data, model, prediction (d) data, prediction, model
  29. 29.Which of these is a prediction? (a) what training builds (b) recorded spoken words (c) naming a new fruit photo (d) the trained program
  30. 30.True or false: “labelled fruit photos” is the model. (a) True (b) False
  31. 31.True or false: “old emails marked spam” is the model. (a) False (b) True
  32. 32.Which of these is the model? (a) tomorrow’s rain guess (b) naming a new fruit photo (c) past weather records (d) the learned patterns
  33. 33.True or false: “recorded spoken words” is training data. (a) False (b) True
  34. 34.⏩ In machine learning, which comes first: naming a new leaf or the learned patterns? (a) naming a new leaf (b) the learned patterns
  35. 35.⏩ In machine learning, which comes first: the learned patterns or naming a new fruit photo? (a) the learned patterns (b) naming a new fruit photo
  36. 36.⏩ In machine learning, which comes first: recorded spoken words or typing a new spoken word? (a) recorded spoken words (b) typing a new spoken word
  37. 37.Which of these is the model? (a) tomorrow’s rain guess (b) recorded spoken words (c) old emails marked spam (d) the trained program
  38. 38.🔁 Training data, the model or a prediction: “past weather records”? (a) the model (b) a prediction (c) training data
  39. 39.🔁 Training data, the model or a prediction: “the trained program”? (a) training data (b) the model (c) a prediction
  40. 40.⏩ In machine learning, which comes first: naming a new fruit photo or old emails marked spam? (a) naming a new fruit photo (b) old emails marked spam

Answer key

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

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