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AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 230 · 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 training data? (a) typing a new spoken word (b) the learned patterns (c) past weather records (d) the trained program
  2. 2.True or false: “what training builds” is the model. (a) True (b) False
  3. 3.🔁 Training data, the model or a prediction: “past weather records”? (a) the model (b) a prediction (c) training data
  4. 4.True or false: “labelled fruit photos” is training data. (a) False (b) True
  5. 5.🧪 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
  6. 6.True or false: “old emails marked spam” is the model. (a) False (b) True
  7. 7.🔁 Training data, the model or a prediction: “tomorrow’s rain guess”? (a) the model (b) a prediction (c) training data
  8. 8.📦 What happens during training? (a) it takes photos (b) it learns patterns (c) it charges up (d) it prints labels
  9. 9.True or false: “typing a new spoken word” is training data. (a) False (b) True
  10. 10.🔁 Training data, the model or a prediction: “flagging a new email”? (a) a prediction (b) the model (c) training data
  11. 11.Which of these is a prediction? (a) labelled fruit photos (b) tomorrow’s rain guess (c) recorded spoken words (d) what training builds
  12. 12.Which of these is training data? (a) typing a new spoken word (b) flagging a new email (c) 500 labelled leaf photos (d) what training builds
  13. 13.🔁 Training data, the model or a prediction: “the trained program”? (a) training data (b) a prediction (c) the model
  14. 14.⏩ In machine learning, which comes first: recorded spoken words or what training builds? (a) recorded spoken words (b) what training builds
  15. 15.True or false: “past weather records” is training data. (a) False (b) True
  16. 16.Which of these is a prediction? (a) old emails marked spam (b) naming a new fruit photo (c) the learned patterns (d) what training builds
  17. 17.⏩ 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
  18. 18.⏩ 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
  19. 19.🔁 What is the right order? (a) prediction, data, model (b) data, model, prediction (c) model, prediction, data (d) data, prediction, model
  20. 20.Which of these is a prediction? (a) past weather records (b) labelled fruit photos (c) recorded spoken words (d) flagging a new email
  21. 21.True or false: “labelled fruit photos” is the model. (a) True (b) False
  22. 22.🔁 Training data, the model or a prediction: “naming a new leaf”? (a) the model (b) a prediction (c) training data
  23. 23.Which of these is training data? (a) flagging a new email (b) the trained program (c) typing a new spoken word (d) old emails marked spam
  24. 24.🔁 Training data, the model or a prediction: “what training builds”? (a) training data (b) a prediction (c) the model
  25. 25.⏩ In machine learning, which comes first: past weather records or naming a new leaf? (a) past weather records (b) naming a new leaf
  26. 26.True or false: “old emails marked spam” is a prediction. (a) False (b) True
  27. 27.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) training data (b) a prediction (c) the model
  28. 28.⏩ In machine learning, which comes first: naming a new leaf or what training builds? (a) naming a new leaf (b) what training builds
  29. 29.🔁 Training data, the model or a prediction: “naming a new fruit photo”? (a) a prediction (b) training data (c) the model
  30. 30.True or false: “the learned patterns” is the model. (a) True (b) False
  31. 31.⏩ In machine learning, which comes first: the learned patterns or past weather records? (a) the learned patterns (b) past weather records
  32. 32.Which of these is the model? (a) flagging a new email (b) what training builds (c) recorded spoken words (d) 500 labelled leaf photos
  33. 33.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) a prediction (b) training data (c) the model
  34. 34.⏩ In machine learning, which comes first: typing a new spoken word or what training builds? (a) typing a new spoken word (b) what training builds
  35. 35.⏩ In machine learning, which comes first: 500 labelled leaf photos or flagging a new email? (a) 500 labelled leaf photos (b) flagging a new email
  36. 36.Which of these is a prediction? (a) labelled fruit photos (b) old emails marked spam (c) 500 labelled leaf photos (d) typing a new spoken word
  37. 37.⏩ In machine learning, which comes first: the trained program or flagging a new email? (a) the trained program (b) flagging a new email
  38. 38.⏩ In machine learning, which comes first: tomorrow’s rain guess or the trained program? (a) tomorrow’s rain guess (b) the trained program
  39. 39.Which of these is the model? (a) tomorrow’s rain guess (b) naming a new leaf (c) the learned patterns (d) flagging a new email
  40. 40.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) the model (b) a prediction (c) training data

Answer key

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

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