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AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 470 · 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) model, prediction, data (c) data, model, prediction (d) prediction, data, model
  2. 2.🔁 Training data, the model or a prediction: “naming a new fruit photo”? (a) the model (b) training data (c) a prediction
  3. 3.🔮 A trained model sees a new photo and says “mango”. This is… (a) a password (b) a label error (c) training data (d) a prediction
  4. 4.Which of these is training data? (a) recorded spoken words (b) typing a new spoken word (c) the trained program (d) flagging a new email
  5. 5.🔁 Training data, the model or a prediction: “the trained program”? (a) training data (b) the model (c) a prediction
  6. 6.🧪 Why test a model on NEW examples? (a) to change its name (b) to delete its data (c) to make it slower (d) to see if it works
  7. 7.📦 What happens during training? (a) it charges up (b) it learns patterns (c) it prints labels (d) it takes photos
  8. 8.🔁 Training data, the model or a prediction: “naming a new leaf”? (a) the model (b) training data (c) a prediction
  9. 9.🔁 Training data, the model or a prediction: “past weather records”? (a) training data (b) the model (c) a prediction
  10. 10.Which of these is training data? (a) flagging a new email (b) naming a new leaf (c) 500 labelled leaf photos (d) the trained program
  11. 11.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) a prediction (b) training data (c) the model
  12. 12.Which of these is training data? (a) typing a new spoken word (b) naming a new leaf (c) the learned patterns (d) old emails marked spam
  13. 13.🔁 Training data, the model or a prediction: “what training builds”? (a) training data (b) the model (c) a prediction
  14. 14.True or false: “what training builds” is the model. (a) True (b) False
  15. 15.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) the model (b) a prediction (c) training data
  16. 16.⏩ In machine learning, which comes first: the learned patterns or flagging a new email? (a) the learned patterns (b) flagging a new email
  17. 17.True or false: “500 labelled leaf photos” is the model. (a) False (b) True
  18. 18.⏩ In machine learning, which comes first: tomorrow’s rain guess or past weather records? (a) tomorrow’s rain guess (b) past weather records
  19. 19.True or false: “500 labelled leaf photos” is training data. (a) True (b) False
  20. 20.True or false: “typing a new spoken word” is a prediction. (a) True (b) False
  21. 21.🔁 Training data, the model or a prediction: “the learned patterns”? (a) a prediction (b) the model (c) training data
  22. 22.⏩ In machine learning, which comes first: past weather records or the trained program? (a) past weather records (b) the trained program
  23. 23.Which of these is training data? (a) past weather records (b) the learned patterns (c) naming a new fruit photo (d) typing a new spoken word
  24. 24.Which of these is a prediction? (a) past weather records (b) recorded spoken words (c) the learned patterns (d) flagging a new email
  25. 25.Which of these is a prediction? (a) old emails marked spam (b) recorded spoken words (c) the trained program (d) naming a new fruit photo
  26. 26.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) the model (b) training data (c) a prediction
  27. 27.⏩ In machine learning, which comes first: the trained program or past weather records? (a) the trained program (b) past weather records
  28. 28.⏩ In machine learning, which comes first: the learned patterns or naming a new leaf? (a) the learned patterns (b) naming a new leaf
  29. 29.Which of these is a prediction? (a) 500 labelled leaf photos (b) old emails marked spam (c) what training builds (d) tomorrow’s rain guess
  30. 30.True or false: “recorded spoken words” is the model. (a) True (b) False
  31. 31.True or false: “tomorrow’s rain guess” is training data. (a) False (b) True
  32. 32.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) the model (b) training data (c) a prediction
  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.🔁 Training data, the model or a prediction: “tomorrow’s rain guess”? (a) training data (b) a prediction (c) the model
  35. 35.True or false: “500 labelled leaf photos” is a prediction. (a) True (b) False
  36. 36.True or false: “naming a new fruit photo” is training data. (a) False (b) True
  37. 37.Which of these is the model? (a) recorded spoken words (b) labelled fruit photos (c) the trained program (d) naming a new leaf
  38. 38.⏩ In machine learning, which comes first: what training builds or past weather records? (a) what training builds (b) past weather records
  39. 39.True or false: “labelled fruit photos” is training data. (a) True (b) False
  40. 40.⏩ In machine learning, which comes first: flagging a new email or the learned patterns? (a) flagging a new email (b) the learned patterns

Answer key

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

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