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AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 776 · 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 happens during training? (a) it learns patterns (b) it takes photos (c) it prints labels (d) it charges up
  2. 2.🔁 What is the right order? (a) data, prediction, model (b) model, prediction, data (c) data, model, prediction (d) prediction, data, model
  3. 3.Which of these is training data? (a) naming a new leaf (b) the trained program (c) the learned patterns (d) recorded spoken words
  4. 4.🧪 Why test a model on NEW examples? (a) to delete its data (b) to make it slower (c) to see if it works (d) to change its name
  5. 5.Which of these is the model? (a) flagging a new email (b) the learned patterns (c) naming a new leaf (d) 500 labelled leaf photos
  6. 6.True or false: “the learned patterns” is training data. (a) False (b) True
  7. 7.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) the model (b) training data (c) a prediction
  8. 8.Which of these is a prediction? (a) labelled fruit photos (b) the learned patterns (c) the trained program (d) flagging a new email
  9. 9.True or false: “typing a new spoken word” is the model. (a) False (b) True
  10. 10.⏩ In machine learning, which comes first: flagging a new email or the learned patterns? (a) flagging a new email (b) the learned patterns
  11. 11.🔁 Training data, the model or a prediction: “tomorrow’s rain guess”? (a) the model (b) training data (c) a prediction
  12. 12.🔁 Training data, the model or a prediction: “past weather records”? (a) training data (b) a prediction (c) the model
  13. 13.🔁 Training data, the model or a prediction: “naming a new fruit photo”? (a) a prediction (b) the model (c) training data
  14. 14.Which of these is training data? (a) flagging a new email (b) naming a new leaf (c) naming a new fruit photo (d) past weather records
  15. 15.Which of these is the model? (a) naming a new fruit photo (b) old emails marked spam (c) the trained program (d) typing a new spoken word
  16. 16.True or false: “tomorrow’s rain guess” is training data. (a) True (b) False
  17. 17.⏩ 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
  18. 18.🔁 Training data, the model or a prediction: “the trained program”? (a) training data (b) a prediction (c) the model
  19. 19.⏩ In machine learning, which comes first: past weather records or naming a new leaf? (a) past weather records (b) naming a new leaf
  20. 20.True or false: “what training builds” is a prediction. (a) True (b) False
  21. 21.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) the model (b) a prediction (c) training data
  22. 22.⏩ In machine learning, which comes first: typing a new spoken word or the trained program? (a) typing a new spoken word (b) the trained program
  23. 23.🔁 Training data, the model or a prediction: “the learned patterns”? (a) a prediction (b) training data (c) the model
  24. 24.True or false: “500 labelled leaf photos” is training data. (a) True (b) False
  25. 25.🔮 A trained model sees a new photo and says “mango”. This is… (a) a prediction (b) a label error (c) training data (d) a password
  26. 26.🔁 Training data, the model or a prediction: “naming a new leaf”? (a) a prediction (b) training data (c) the model
  27. 27.Which of these is a prediction? (a) the trained program (b) what training builds (c) naming a new fruit photo (d) recorded spoken words
  28. 28.Which of these is the model? (a) naming a new leaf (b) what training builds (c) flagging a new email (d) typing a new spoken word
  29. 29.True or false: “the trained program” is training data. (a) True (b) False
  30. 30.True or false: “naming a new fruit photo” is the model. (a) False (b) True
  31. 31.Which of these is training data? (a) tomorrow’s rain guess (b) old emails marked spam (c) typing a new spoken word (d) flagging a new email
  32. 32.True or false: “the learned patterns” is the model. (a) False (b) True
  33. 33.⏩ In machine learning, which comes first: what training builds or naming a new fruit photo? (a) what training builds (b) naming a new fruit photo
  34. 34.True or false: “naming a new fruit photo” is a prediction. (a) False (b) True
  35. 35.Which of these is a prediction? (a) old emails marked spam (b) the learned patterns (c) the trained program (d) naming a new leaf
  36. 36.True or false: “naming a new fruit photo” is training data. (a) False (b) True
  37. 37.Which of these is training data? (a) what training builds (b) the learned patterns (c) flagging a new email (d) 500 labelled leaf photos
  38. 38.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) the model (b) training data (c) a prediction
  39. 39.True or false: “old emails marked spam” is a prediction. (a) False (b) True
  40. 40.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) the model (b) a prediction (c) training data

Answer key

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

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