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AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 384 · 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.🔁 Training data, the model or a prediction: “naming a new fruit photo”? (a) training data (b) the model (c) a prediction
  2. 2.🔁 Training data, the model or a prediction: “the learned patterns”? (a) a prediction (b) the model (c) training data
  3. 3.🔁 What is the right order? (a) prediction, data, model (b) data, model, prediction (c) model, prediction, data (d) data, prediction, model
  4. 4.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) training data (b) the model (c) a prediction
  5. 5.⏩ In machine learning, which comes first: tomorrow’s rain guess or the learned patterns? (a) tomorrow’s rain guess (b) the learned patterns
  6. 6.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) training data (b) a prediction (c) the model
  7. 7.Which of these is a prediction? (a) 500 labelled leaf photos (b) naming a new fruit photo (c) the trained program (d) recorded spoken words
  8. 8.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) the model (b) a prediction (c) training data
  9. 9.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) training data (b) a prediction (c) the model
  10. 10.Which of these is the model? (a) recorded spoken words (b) naming a new fruit photo (c) flagging a new email (d) the learned patterns
  11. 11.True or false: “typing a new spoken word” is the model. (a) True (b) False
  12. 12.🔁 Training data, the model or a prediction: “flagging a new email”? (a) the model (b) training data (c) a prediction
  13. 13.🔁 Training data, the model or a prediction: “what training builds”? (a) a prediction (b) the model (c) training data
  14. 14.True or false: “the learned patterns” is training data. (a) False (b) True
  15. 15.🔮 A trained model sees a new photo and says “mango”. This is… (a) a password (b) a prediction (c) training data (d) a label error
  16. 16.🧪 Why test a model on NEW examples? (a) to change its name (b) to delete its data (c) to see if it works (d) to make it slower
  17. 17.Which of these is training data? (a) what training builds (b) naming a new leaf (c) tomorrow’s rain guess (d) old emails marked spam
  18. 18.Which of these is training data? (a) naming a new leaf (b) what training builds (c) typing a new spoken word (d) labelled fruit photos
  19. 19.📦 What happens during training? (a) it takes photos (b) it learns patterns (c) it charges up (d) it prints labels
  20. 20.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) a prediction (b) the model (c) training data
  21. 21.True or false: “naming a new fruit photo” is the model. (a) False (b) True
  22. 22.🔁 Training data, the model or a prediction: “past weather records”? (a) training data (b) a prediction (c) the model
  23. 23.Which of these is training data? (a) naming a new fruit photo (b) recorded spoken words (c) flagging a new email (d) tomorrow’s rain guess
  24. 24.Which of these is the model? (a) flagging a new email (b) labelled fruit photos (c) the trained program (d) naming a new leaf
  25. 25.True or false: “what training builds” is the model. (a) True (b) False
  26. 26.⏩ 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
  27. 27.True or false: “past weather records” is training data. (a) False (b) True
  28. 28.Which of these is the model? (a) flagging a new email (b) what training builds (c) labelled fruit photos (d) past weather records
  29. 29.⏩ In machine learning, which comes first: what training builds or typing a new spoken word? (a) what training builds (b) typing a new spoken word
  30. 30.True or false: “labelled fruit photos” is training data. (a) False (b) True
  31. 31.⏩ In machine learning, which comes first: naming a new leaf or the learned patterns? (a) naming a new leaf (b) the learned patterns
  32. 32.True or false: “tomorrow’s rain guess” is training data. (a) True (b) False
  33. 33.Which of these is training data? (a) what training builds (b) flagging a new email (c) naming a new leaf (d) 500 labelled leaf photos
  34. 34.True or false: “old emails marked spam” is training data. (a) True (b) False
  35. 35.Which of these is a prediction? (a) naming a new leaf (b) 500 labelled leaf photos (c) the learned patterns (d) old emails marked spam
  36. 36.True or false: “typing a new spoken word” is training data. (a) True (b) False
  37. 37.⏩ In machine learning, which comes first: what training builds or labelled fruit photos? (a) what training builds (b) labelled fruit photos
  38. 38.Which of these is a prediction? (a) 500 labelled leaf photos (b) the trained program (c) flagging a new email (d) recorded spoken words
  39. 39.True or false: “500 labelled leaf photos” is a prediction. (a) True (b) False
  40. 40.🔁 Training data, the model or a prediction: “naming a new leaf”? (a) the model (b) a prediction (c) training data

Answer key

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

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