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AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 645 · 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 a prediction? (a) old emails marked spam (b) recorded spoken words (c) 500 labelled leaf photos (d) tomorrow’s rain guess
  2. 2.Which of these is a prediction? (a) recorded spoken words (b) the learned patterns (c) naming a new fruit photo (d) the trained program
  3. 3.🔁 What is the right order? (a) data, prediction, model (b) data, model, prediction (c) model, prediction, data (d) prediction, data, model
  4. 4.Which of these is the model? (a) old emails marked spam (b) typing a new spoken word (c) past weather records (d) what training builds
  5. 5.⏩ 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
  6. 6.Which of these is training data? (a) the learned patterns (b) what training builds (c) past weather records (d) the trained program
  7. 7.📦 What happens during training? (a) it learns patterns (b) it takes photos (c) it prints labels (d) it charges up
  8. 8.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) a prediction (b) the model (c) training data
  9. 9.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) training data (b) a prediction (c) the model
  10. 10.True or false: “typing a new spoken word” is a prediction. (a) True (b) False
  11. 11.Which of these is a prediction? (a) recorded spoken words (b) the trained program (c) past weather records (d) flagging a new email
  12. 12.Which of these is the model? (a) old emails marked spam (b) tomorrow’s rain guess (c) the learned patterns (d) flagging a new email
  13. 13.🔁 Training data, the model or a prediction: “tomorrow’s rain guess”? (a) the model (b) a prediction (c) training data
  14. 14.🧪 Why test a model on NEW examples? (a) to see if it works (b) to delete its data (c) to change its name (d) to make it slower
  15. 15.⏩ In machine learning, which comes first: tomorrow’s rain guess or past weather records? (a) tomorrow’s rain guess (b) past weather records
  16. 16.🔁 Training data, the model or a prediction: “the trained program”? (a) a prediction (b) the model (c) training data
  17. 17.🔁 Training data, the model or a prediction: “naming a new leaf”? (a) the model (b) training data (c) a prediction
  18. 18.🔁 Training data, the model or a prediction: “what training builds”? (a) the model (b) training data (c) a prediction
  19. 19.⏩ In machine learning, which comes first: the learned patterns or tomorrow’s rain guess? (a) the learned patterns (b) tomorrow’s rain guess
  20. 20.🔁 Training data, the model or a prediction: “the learned patterns”? (a) the model (b) training data (c) a prediction
  21. 21.⏩ In machine learning, which comes first: the trained program or naming a new leaf? (a) the trained program (b) naming a new leaf
  22. 22.True or false: “naming a new leaf” is training data. (a) True (b) False
  23. 23.🔮 A trained model sees a new photo and says “mango”. This is… (a) training data (b) a password (c) a label error (d) a prediction
  24. 24.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) the model (b) a prediction (c) training data
  25. 25.⏩ 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
  26. 26.True or false: “tomorrow’s rain guess” is a prediction. (a) True (b) False
  27. 27.⏩ In machine learning, which comes first: labelled fruit photos or the trained program? (a) labelled fruit photos (b) the trained program
  28. 28.⏩ In machine learning, which comes first: flagging a new email or the learned patterns? (a) flagging a new email (b) the learned patterns
  29. 29.Which of these is training data? (a) labelled fruit photos (b) the learned patterns (c) flagging a new email (d) what training builds
  30. 30.True or false: “past weather records” is training data. (a) True (b) False
  31. 31.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) a prediction (b) training data (c) the model
  32. 32.Which of these is a prediction? (a) naming a new leaf (b) old emails marked spam (c) the learned patterns (d) 500 labelled leaf photos
  33. 33.True or false: “the learned patterns” is the model. (a) False (b) True
  34. 34.True or false: “recorded spoken words” is the model. (a) True (b) False
  35. 35.True or false: “flagging a new email” is a prediction. (a) True (b) False
  36. 36.⏩ 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
  37. 37.⏩ In machine learning, which comes first: tomorrow’s rain guess or the learned patterns? (a) tomorrow’s rain guess (b) the learned patterns
  38. 38.⏩ In machine learning, which comes first: past weather records or naming a new fruit photo? (a) past weather records (b) naming a new fruit photo
  39. 39.⏩ In machine learning, which comes first: past weather records or what training builds? (a) past weather records (b) what training builds
  40. 40.True or false: “tomorrow’s rain guess” is training data. (a) False (b) True

Answer key

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

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