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AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 623 · 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: “typing a new spoken word”? (a) a prediction (b) the model (c) training data
  2. 2.Which of these is training data? (a) naming a new fruit photo (b) flagging a new email (c) typing a new spoken word (d) recorded spoken words
  3. 3.True or false: “flagging a new email” is training data. (a) False (b) True
  4. 4.True or false: “typing a new spoken word” is a prediction. (a) True (b) False
  5. 5.Which of these is a prediction? (a) the learned patterns (b) recorded spoken words (c) naming a new fruit photo (d) old emails marked spam
  6. 6.🧪 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
  7. 7.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) training data (b) a prediction (c) the model
  8. 8.📦 What happens during training? (a) it takes photos (b) it learns patterns (c) it prints labels (d) it charges up
  9. 9.🔁 Training data, the model or a prediction: “flagging a new email”? (a) a prediction (b) the model (c) training data
  10. 10.⏩ In machine learning, which comes first: the learned patterns or naming a new fruit photo? (a) the learned patterns (b) naming a new fruit photo
  11. 11.True or false: “500 labelled leaf photos” is the model. (a) False (b) True
  12. 12.🔁 Training data, the model or a prediction: “tomorrow’s rain guess”? (a) the model (b) training data (c) a prediction
  13. 13.🔮 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
  14. 14.⏩ In machine learning, which comes first: naming a new leaf or 500 labelled leaf photos? (a) naming a new leaf (b) 500 labelled leaf photos
  15. 15.Which of these is a prediction? (a) the learned patterns (b) what training builds (c) naming a new leaf (d) recorded spoken words
  16. 16.⏩ In machine learning, which comes first: flagging a new email or 500 labelled leaf photos? (a) flagging a new email (b) 500 labelled leaf photos
  17. 17.🔁 Training data, the model or a prediction: “naming a new leaf”? (a) the model (b) training data (c) a prediction
  18. 18.True or false: “tomorrow’s rain guess” is a prediction. (a) False (b) True
  19. 19.🔁 Training data, the model or a prediction: “the learned patterns”? (a) training data (b) the model (c) a prediction
  20. 20.🔁 What is the right order? (a) prediction, data, model (b) data, prediction, model (c) data, model, prediction (d) model, prediction, data
  21. 21.⏩ In machine learning, which comes first: the learned patterns or 500 labelled leaf photos? (a) the learned patterns (b) 500 labelled leaf photos
  22. 22.Which of these is training data? (a) tomorrow’s rain guess (b) naming a new fruit photo (c) past weather records (d) the learned patterns
  23. 23.🔁 Training data, the model or a prediction: “naming a new fruit photo”? (a) a prediction (b) the model (c) training data
  24. 24.⏩ In machine learning, which comes first: recorded spoken words or flagging a new email? (a) recorded spoken words (b) flagging a new email
  25. 25.Which of these is a prediction? (a) what training builds (b) tomorrow’s rain guess (c) old emails marked spam (d) recorded spoken words
  26. 26.True or false: “the learned patterns” is the model. (a) False (b) True
  27. 27.⏩ In machine learning, which comes first: what training builds or flagging a new email? (a) what training builds (b) flagging a new email
  28. 28.True or false: “tomorrow’s rain guess” is training data. (a) False (b) True
  29. 29.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) the model (b) a prediction (c) training data
  30. 30.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) a prediction (b) the model (c) training data
  31. 31.True or false: “the learned patterns” is training data. (a) True (b) False
  32. 32.Which of these is training data? (a) naming a new fruit photo (b) old emails marked spam (c) the trained program (d) what training builds
  33. 33.True or false: “naming a new leaf” is the model. (a) True (b) False
  34. 34.Which of these is the model? (a) what training builds (b) labelled fruit photos (c) recorded spoken words (d) naming a new fruit photo
  35. 35.True or false: “the learned patterns” is a prediction. (a) False (b) True
  36. 36.True or false: “recorded spoken words” is training data. (a) True (b) False
  37. 37.Which of these is training data? (a) 500 labelled leaf photos (b) the learned patterns (c) the trained program (d) naming a new leaf
  38. 38.🔁 Training data, the model or a prediction: “what training builds”? (a) training data (b) a prediction (c) the model
  39. 39.True or false: “500 labelled leaf photos” is training data. (a) True (b) False
  40. 40.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) a prediction (b) training data (c) the model

Answer key

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

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