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AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 462 · 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 the model? (a) naming a new leaf (b) flagging a new email (c) the learned patterns (d) recorded spoken words
  2. 2.🔮 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
  3. 3.True or false: “typing a new spoken word” is training data. (a) False (b) True
  4. 4.True or false: “500 labelled leaf photos” is a prediction. (a) True (b) False
  5. 5.🧪 Why test a model on NEW examples? (a) to delete its data (b) to make it slower (c) to change its name (d) to see if it works
  6. 6.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) training data (b) the model (c) a prediction
  7. 7.True or false: “old emails marked spam” is training data. (a) False (b) True
  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.Which of these is the model? (a) what training builds (b) 500 labelled leaf photos (c) naming a new leaf (d) old emails marked spam
  10. 10.True or false: “recorded spoken words” is training data. (a) True (b) False
  11. 11.⏩ In machine learning, which comes first: recorded spoken words or naming a new fruit photo? (a) recorded spoken words (b) naming a new fruit photo
  12. 12.⏩ In machine learning, which comes first: the trained program or naming a new fruit photo? (a) the trained program (b) naming a new fruit photo
  13. 13.True or false: “labelled fruit photos” is the model. (a) False (b) True
  14. 14.📦 What happens during training? (a) it prints labels (b) it learns patterns (c) it takes photos (d) it charges up
  15. 15.🔁 Training data, the model or a prediction: “naming a new leaf”? (a) the model (b) training data (c) a prediction
  16. 16.Which of these is a prediction? (a) flagging a new email (b) recorded spoken words (c) past weather records (d) the learned patterns
  17. 17.Which of these is a prediction? (a) 500 labelled leaf photos (b) old emails marked spam (c) naming a new fruit photo (d) past weather records
  18. 18.⏩ In machine learning, which comes first: what training builds or tomorrow’s rain guess? (a) what training builds (b) tomorrow’s rain guess
  19. 19.⏩ In machine learning, which comes first: naming a new fruit photo or the trained program? (a) naming a new fruit photo (b) the trained program
  20. 20.Which of these is a prediction? (a) 500 labelled leaf photos (b) labelled fruit photos (c) recorded spoken words (d) naming a new leaf
  21. 21.🔁 Training data, the model or a prediction: “naming a new fruit photo”? (a) the model (b) training data (c) a prediction
  22. 22.Which of these is training data? (a) what training builds (b) tomorrow’s rain guess (c) past weather records (d) the trained program
  23. 23.⏩ In machine learning, which comes first: what training builds or flagging a new email? (a) what training builds (b) flagging a new email
  24. 24.True or false: “500 labelled leaf photos” is training data. (a) False (b) True
  25. 25.⏩ In machine learning, which comes first: the learned patterns or old emails marked spam? (a) the learned patterns (b) old emails marked spam
  26. 26.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) a prediction (b) the model (c) training data
  27. 27.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) the model (b) a prediction (c) training data
  28. 28.Which of these is training data? (a) tomorrow’s rain guess (b) the trained program (c) recorded spoken words (d) the learned patterns
  29. 29.True or false: “flagging a new email” is a prediction. (a) True (b) False
  30. 30.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) training data (b) a prediction (c) the model
  31. 31.⏩ In machine learning, which comes first: labelled fruit photos or what training builds? (a) labelled fruit photos (b) what training builds
  32. 32.⏩ In machine learning, which comes first: past weather records or what training builds? (a) past weather records (b) what training builds
  33. 33.True or false: “the learned patterns” is the model. (a) False (b) True
  34. 34.Which of these is training data? (a) naming a new fruit photo (b) flagging a new email (c) naming a new leaf (d) old emails marked spam
  35. 35.Which of these is the model? (a) 500 labelled leaf photos (b) recorded spoken words (c) naming a new fruit photo (d) the trained program
  36. 36.🔁 What is the right order? (a) data, prediction, model (b) prediction, data, model (c) data, model, prediction (d) model, prediction, data
  37. 37.⏩ In machine learning, which comes first: flagging a new email or labelled fruit photos? (a) flagging a new email (b) labelled fruit photos
  38. 38.True or false: “naming a new fruit photo” is training data. (a) True (b) False
  39. 39.⏩ In machine learning, which comes first: the learned patterns or typing a new spoken word? (a) the learned patterns (b) typing a new spoken word
  40. 40.⏩ In machine learning, which comes first: the learned patterns or naming a new leaf? (a) the learned patterns (b) naming a new leaf

Answer key

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

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