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AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 988 · 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.🔁 What is the right order? (a) data, prediction, model (b) data, model, prediction (c) model, prediction, data (d) prediction, data, model
  2. 2.True or false: “past weather records” is the model. (a) True (b) False
  3. 3.⏩ 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
  4. 4.🔮 A trained model sees a new photo and says “mango”. This is… (a) a prediction (b) a password (c) a label error (d) training data
  5. 5.⏩ In machine learning, which comes first: what training builds or 500 labelled leaf photos? (a) what training builds (b) 500 labelled leaf photos
  6. 6.🔁 Training data, the model or a prediction: “naming a new fruit photo”? (a) the model (b) a prediction (c) training data
  7. 7.True or false: “500 labelled leaf photos” is a prediction. (a) False (b) True
  8. 8.⏩ In machine learning, which comes first: old emails marked spam or the learned patterns? (a) old emails marked spam (b) the learned patterns
  9. 9.⏩ In machine learning, which comes first: naming a new fruit photo or what training builds? (a) naming a new fruit photo (b) what training builds
  10. 10.Which of these is a prediction? (a) flagging a new email (b) labelled fruit photos (c) 500 labelled leaf photos (d) recorded spoken words
  11. 11.True or false: “flagging a new email” is training data. (a) False (b) True
  12. 12.⏩ In machine learning, which comes first: tomorrow’s rain guess or the learned patterns? (a) tomorrow’s rain guess (b) the learned patterns
  13. 13.True or false: “what training builds” is a prediction. (a) False (b) True
  14. 14.Which of these is training data? (a) what training builds (b) typing a new spoken word (c) labelled fruit photos (d) the trained program
  15. 15.True or false: “what training builds” is the model. (a) False (b) True
  16. 16.⏩ In machine learning, which comes first: flagging a new email or recorded spoken words? (a) flagging a new email (b) recorded spoken words
  17. 17.⏩ In machine learning, which comes first: 500 labelled leaf photos or the learned patterns? (a) 500 labelled leaf photos (b) the learned patterns
  18. 18.True or false: “recorded spoken words” is a prediction. (a) True (b) False
  19. 19.Which of these is the model? (a) the trained program (b) flagging a new email (c) naming a new leaf (d) old emails marked spam
  20. 20.⏩ In machine learning, which comes first: naming a new leaf or old emails marked spam? (a) naming a new leaf (b) old emails marked spam
  21. 21.Which of these is training data? (a) the learned patterns (b) naming a new leaf (c) 500 labelled leaf photos (d) naming a new fruit photo
  22. 22.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) a prediction (b) the model (c) training data
  23. 23.⏩ In machine learning, which comes first: the trained program or naming a new leaf? (a) the trained program (b) naming a new leaf
  24. 24.Which of these is the model? (a) old emails marked spam (b) labelled fruit photos (c) the learned patterns (d) 500 labelled leaf photos
  25. 25.🔁 Training data, the model or a prediction: “naming a new leaf”? (a) a prediction (b) the model (c) training data
  26. 26.True or false: “old emails marked spam” is the model. (a) False (b) True
  27. 27.⏩ In machine learning, which comes first: the learned patterns or old emails marked spam? (a) the learned patterns (b) old emails marked spam
  28. 28.⏩ In machine learning, which comes first: typing a new spoken word or the learned patterns? (a) typing a new spoken word (b) the learned patterns
  29. 29.🧪 Why test a model on NEW examples? (a) to make it slower (b) to see if it works (c) to delete its data (d) to change its name
  30. 30.True or false: “the trained program” is the model. (a) False (b) True
  31. 31.True or false: “recorded spoken words” is training data. (a) True (b) False
  32. 32.Which of these is the model? (a) typing a new spoken word (b) flagging a new email (c) what training builds (d) past weather records
  33. 33.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) training data (b) a prediction (c) the model
  34. 34.⏩ In machine learning, which comes first: flagging a new email or old emails marked spam? (a) flagging a new email (b) old emails marked spam
  35. 35.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) a prediction (b) the model (c) training data
  36. 36.True or false: “tomorrow’s rain guess” is training data. (a) False (b) True
  37. 37.Which of these is a prediction? (a) 500 labelled leaf photos (b) past weather records (c) old emails marked spam (d) typing a new spoken word
  38. 38.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) a prediction (b) training data (c) the model
  39. 39.True or false: “labelled fruit photos” is a prediction. (a) True (b) False
  40. 40.True or false: “what training builds” is training data. (a) False (b) True

Answer key

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

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