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AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 457 · 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: “recorded spoken words”? (a) the model (b) training data (c) a prediction
  2. 2.Which of these is the model? (a) flagging a new email (b) labelled fruit photos (c) naming a new fruit photo (d) what training builds
  3. 3.🧪 Why test a model on NEW examples? (a) to see if it works (b) to change its name (c) to make it slower (d) to delete its data
  4. 4.True or false: “500 labelled leaf photos” is training data. (a) True (b) False
  5. 5.True or false: “what training builds” is a prediction. (a) True (b) False
  6. 6.Which of these is a prediction? (a) naming a new leaf (b) recorded spoken words (c) the learned patterns (d) what training builds
  7. 7.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) the model (b) training data (c) a prediction
  8. 8.⏩ In machine learning, which comes first: recorded spoken words or tomorrow’s rain guess? (a) recorded spoken words (b) tomorrow’s rain guess
  9. 9.⏩ In machine learning, which comes first: tomorrow’s rain guess or the trained program? (a) tomorrow’s rain guess (b) the trained program
  10. 10.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) training data (b) a prediction (c) the model
  11. 11.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) the model (b) training data (c) a prediction
  12. 12.🔁 Training data, the model or a prediction: “what training builds”? (a) the model (b) a prediction (c) training data
  13. 13.Which of these is training data? (a) tomorrow’s rain guess (b) labelled fruit photos (c) flagging a new email (d) naming a new leaf
  14. 14.⏩ In machine learning, which comes first: recorded spoken words or naming a new leaf? (a) recorded spoken words (b) naming a new leaf
  15. 15.🔮 A trained model sees a new photo and says “mango”. This is… (a) training data (b) a label error (c) a prediction (d) a password
  16. 16.Which of these is the model? (a) 500 labelled leaf photos (b) old emails marked spam (c) the learned patterns (d) typing a new spoken word
  17. 17.🔁 Training data, the model or a prediction: “past weather records”? (a) the model (b) a prediction (c) training data
  18. 18.Which of these is training data? (a) flagging a new email (b) what training builds (c) the learned patterns (d) past weather records
  19. 19.True or false: “recorded spoken words” is the model. (a) False (b) True
  20. 20.🔁 What is the right order? (a) data, model, prediction (b) prediction, data, model (c) data, prediction, model (d) model, prediction, data
  21. 21.True or false: “naming a new leaf” is a prediction. (a) True (b) False
  22. 22.⏩ In machine learning, which comes first: 500 labelled leaf photos or naming a new leaf? (a) 500 labelled leaf photos (b) naming a new leaf
  23. 23.⏩ In machine learning, which comes first: flagging a new email or labelled fruit photos? (a) flagging a new email (b) labelled fruit photos
  24. 24.📦 What happens during training? (a) it takes photos (b) it prints labels (c) it charges up (d) it learns patterns
  25. 25.⏩ In machine learning, which comes first: past weather records or the trained program? (a) past weather records (b) the trained program
  26. 26.🔁 Training data, the model or a prediction: “tomorrow’s rain guess”? (a) training data (b) a prediction (c) the model
  27. 27.True or false: “recorded spoken words” is training data. (a) True (b) False
  28. 28.⏩ In machine learning, which comes first: old emails marked spam or typing a new spoken word? (a) old emails marked spam (b) typing a new spoken word
  29. 29.True or false: “typing a new spoken word” is training data. (a) False (b) True
  30. 30.⏩ 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
  31. 31.⏩ In machine learning, which comes first: flagging a new email or what training builds? (a) flagging a new email (b) what training builds
  32. 32.Which of these is a prediction? (a) the trained program (b) labelled fruit photos (c) naming a new fruit photo (d) old emails marked spam
  33. 33.🔁 Training data, the model or a prediction: “the learned patterns”? (a) the model (b) a prediction (c) training data
  34. 34.Which of these is the model? (a) naming a new fruit photo (b) naming a new leaf (c) the trained program (d) past weather records
  35. 35.⏩ In machine learning, which comes first: what training builds or past weather records? (a) what training builds (b) past weather records
  36. 36.⏩ In machine learning, which comes first: naming a new fruit photo or the learned patterns? (a) naming a new fruit photo (b) the learned patterns
  37. 37.True or false: “what training builds” is the model. (a) True (b) False
  38. 38.Which of these is training data? (a) old emails marked spam (b) typing a new spoken word (c) the learned patterns (d) the trained program
  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.🔁 Training data, the model or a prediction: “naming a new fruit photo”? (a) the model (b) a prediction (c) training data

Answer key

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

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