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AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 828 · 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.🔮 A trained model sees a new photo and says “mango”. This is… (a) a prediction (b) training data (c) a label error (d) a password
  2. 2.Which of these is training data? (a) flagging a new email (b) 500 labelled leaf photos (c) typing a new spoken word (d) the learned patterns
  3. 3.🔁 Training data, the model or a prediction: “naming a new leaf”? (a) training data (b) the model (c) a prediction
  4. 4.🧪 Why test a model on NEW examples? (a) to make it slower (b) to see if it works (c) to change its name (d) to delete its data
  5. 5.⏩ 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
  6. 6.Which of these is a prediction? (a) recorded spoken words (b) past weather records (c) naming a new fruit photo (d) what training builds
  7. 7.🔁 Training data, the model or a prediction: “what training builds”? (a) training data (b) a prediction (c) the model
  8. 8.True or false: “typing a new spoken word” is a prediction. (a) True (b) False
  9. 9.Which of these is training data? (a) flagging a new email (b) what training builds (c) the learned patterns (d) labelled fruit photos
  10. 10.📦 What happens during training? (a) it takes photos (b) it prints labels (c) it charges up (d) it learns patterns
  11. 11.True or false: “labelled fruit photos” is the model. (a) False (b) True
  12. 12.⏩ In machine learning, which comes first: labelled fruit photos or typing a new spoken word? (a) labelled fruit photos (b) typing a new spoken word
  13. 13.⏩ In machine learning, which comes first: naming a new leaf or what training builds? (a) naming a new leaf (b) what training builds
  14. 14.⏩ In machine learning, which comes first: flagging a new email or 500 labelled leaf photos? (a) flagging a new email (b) 500 labelled leaf photos
  15. 15.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) the model (b) a prediction (c) training data
  16. 16.Which of these is the model? (a) what training builds (b) recorded spoken words (c) 500 labelled leaf photos (d) naming a new leaf
  17. 17.True or false: “old emails marked spam” is training data. (a) True (b) False
  18. 18.True or false: “naming a new leaf” is a prediction. (a) False (b) True
  19. 19.⏩ In machine learning, which comes first: typing a new spoken word or past weather records? (a) typing a new spoken word (b) past weather records
  20. 20.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) a prediction (b) the model (c) training data
  21. 21.🔁 Training data, the model or a prediction: “the trained program”? (a) a prediction (b) training data (c) the model
  22. 22.⏩ In machine learning, which comes first: the trained program or past weather records? (a) the trained program (b) past weather records
  23. 23.⏩ In machine learning, which comes first: past weather records or the learned patterns? (a) past weather records (b) the learned patterns
  24. 24.🔁 What is the right order? (a) model, prediction, data (b) data, model, prediction (c) prediction, data, model (d) data, prediction, model
  25. 25.True or false: “the trained program” is training data. (a) False (b) True
  26. 26.⏩ In machine learning, which comes first: typing a new spoken word or old emails marked spam? (a) typing a new spoken word (b) old emails marked spam
  27. 27.⏩ In machine learning, which comes first: the trained program or flagging a new email? (a) the trained program (b) flagging a new email
  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.True or false: “flagging a new email” is a prediction. (a) True (b) False
  30. 30.True or false: “flagging a new email” is training data. (a) False (b) True
  31. 31.True or false: “naming a new fruit photo” is the model. (a) True (b) False
  32. 32.⏩ In machine learning, which comes first: the learned patterns or past weather records? (a) the learned patterns (b) past weather records
  33. 33.True or false: “tomorrow’s rain guess” is the model. (a) True (b) False
  34. 34.True or false: “recorded spoken words” is training data. (a) False (b) True
  35. 35.True or false: “labelled fruit photos” is a prediction. (a) True (b) False
  36. 36.⏩ In machine learning, which comes first: the trained program or labelled fruit photos? (a) the trained program (b) labelled fruit photos
  37. 37.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) the model (b) a prediction (c) training data
  38. 38.⏩ In machine learning, which comes first: what training builds or naming a new leaf? (a) what training builds (b) naming a new leaf
  39. 39.⏩ In machine learning, which comes first: the learned patterns or naming a new leaf? (a) the learned patterns (b) naming a new leaf
  40. 40.Which of these is training data? (a) naming a new fruit photo (b) the learned patterns (c) old emails marked spam (d) the trained program

Answer key

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

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