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AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 800 · 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: naming a new leaf or the learned patterns? (a) naming a new leaf (b) the learned patterns
  2. 2.True or false: “typing a new spoken word” is the model. (a) True (b) False
  3. 3.⏩ 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
  4. 4.🧪 Why test a model on NEW examples? (a) to change its name (b) to see if it works (c) to delete its data (d) to make it slower
  5. 5.Which of these is training data? (a) the trained program (b) 500 labelled leaf photos (c) what training builds (d) naming a new leaf
  6. 6.⏩ In machine learning, which comes first: past weather records or flagging a new email? (a) past weather records (b) flagging a new email
  7. 7.⏩ 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
  8. 8.🔁 Training data, the model or a prediction: “flagging a new email”? (a) a prediction (b) training data (c) the model
  9. 9.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) a prediction (b) training data (c) the model
  10. 10.⏩ In machine learning, which comes first: typing a new spoken word or the trained program? (a) typing a new spoken word (b) the trained program
  11. 11.🔁 Training data, the model or a prediction: “naming a new fruit photo”? (a) the model (b) training data (c) a prediction
  12. 12.⏩ In machine learning, which comes first: old emails marked spam or naming a new leaf? (a) old emails marked spam (b) naming a new leaf
  13. 13.🔁 Training data, the model or a prediction: “what training builds”? (a) the model (b) training data (c) a prediction
  14. 14.🔁 What is the right order? (a) prediction, data, model (b) data, model, prediction (c) model, prediction, data (d) data, prediction, model
  15. 15.⏩ In machine learning, which comes first: the trained program or naming a new leaf? (a) the trained program (b) naming a new leaf
  16. 16.🔮 A trained model sees a new photo and says “mango”. This is… (a) training data (b) a prediction (c) a password (d) a label error
  17. 17.⏩ In machine learning, which comes first: labelled fruit photos or tomorrow’s rain guess? (a) labelled fruit photos (b) tomorrow’s rain guess
  18. 18.🔁 Training data, the model or a prediction: “past weather records”? (a) the model (b) a prediction (c) training data
  19. 19.⏩ In machine learning, which comes first: the learned patterns or naming a new leaf? (a) the learned patterns (b) naming a new leaf
  20. 20.Which of these is training data? (a) naming a new leaf (b) tomorrow’s rain guess (c) flagging a new email (d) labelled fruit photos
  21. 21.Which of these is the model? (a) typing a new spoken word (b) past weather records (c) naming a new leaf (d) the learned patterns
  22. 22.True or false: “naming a new fruit photo” is training data. (a) True (b) False
  23. 23.⏩ In machine learning, which comes first: recorded spoken words or the learned patterns? (a) recorded spoken words (b) the learned patterns
  24. 24.⏩ 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
  25. 25.Which of these is a prediction? (a) old emails marked spam (b) past weather records (c) tomorrow’s rain guess (d) 500 labelled leaf photos
  26. 26.True or false: “typing a new spoken word” is training data. (a) False (b) True
  27. 27.True or false: “the trained program” is training data. (a) False (b) True
  28. 28.Which of these is a prediction? (a) old emails marked spam (b) 500 labelled leaf photos (c) what training builds (d) flagging a new email
  29. 29.Which of these is a prediction? (a) naming a new fruit photo (b) labelled fruit photos (c) 500 labelled leaf photos (d) old emails marked spam
  30. 30.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) training data (b) the model (c) a prediction
  31. 31.⏩ In machine learning, which comes first: naming a new fruit photo or 500 labelled leaf photos? (a) naming a new fruit photo (b) 500 labelled leaf photos
  32. 32.🔁 Training data, the model or a prediction: “the learned patterns”? (a) training data (b) a prediction (c) the model
  33. 33.⏩ In machine learning, which comes first: tomorrow’s rain guess or the learned patterns? (a) tomorrow’s rain guess (b) the learned patterns
  34. 34.Which of these is the model? (a) typing a new spoken word (b) the trained program (c) 500 labelled leaf photos (d) labelled fruit photos
  35. 35.True or false: “tomorrow’s rain guess” is a prediction. (a) True (b) False
  36. 36.⏩ In machine learning, which comes first: 500 labelled leaf photos or what training builds? (a) 500 labelled leaf photos (b) what training builds
  37. 37.⏩ 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
  38. 38.🔁 Training data, the model or a prediction: “naming a new leaf”? (a) the model (b) a prediction (c) training data
  39. 39.Which of these is training data? (a) the learned patterns (b) flagging a new email (c) old emails marked spam (d) typing a new spoken word
  40. 40.True or false: “what training builds” is training data. (a) False (b) True

Answer key

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

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