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AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 473 · 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.Which of these is the model? (a) the learned patterns (b) naming a new fruit photo (c) tomorrow’s rain guess (d) past weather records
  2. 2.🔁 Training data, the model or a prediction: “naming a new fruit photo”? (a) training data (b) the model (c) a prediction
  3. 3.⏩ In machine learning, which comes first: what training builds or flagging a new email? (a) what training builds (b) flagging a new email
  4. 4.Which of these is a prediction? (a) old emails marked spam (b) recorded spoken words (c) what training builds (d) naming a new fruit photo
  5. 5.🔁 Training data, the model or a prediction: “past weather records”? (a) the model (b) training data (c) a prediction
  6. 6.🔁 What is the right order? (a) prediction, data, model (b) data, prediction, model (c) data, model, prediction (d) model, prediction, data
  7. 7.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) training data (b) a prediction (c) the model
  8. 8.🔁 Training data, the model or a prediction: “the trained program”? (a) training data (b) a prediction (c) the model
  9. 9.⏩ 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
  10. 10.True or false: “naming a new fruit photo” is a prediction. (a) False (b) True
  11. 11.🔮 A trained model sees a new photo and says “mango”. This is… (a) a label error (b) training data (c) a password (d) a prediction
  12. 12.🔁 Training data, the model or a prediction: “tomorrow’s rain guess”? (a) training data (b) a prediction (c) the model
  13. 13.True or false: “naming a new leaf” is a prediction. (a) True (b) False
  14. 14.True or false: “naming a new leaf” is the model. (a) True (b) False
  15. 15.🧪 Why test a model on NEW examples? (a) to delete its data (b) to make it slower (c) to change its name (d) to see if it works
  16. 16.📦 What happens during training? (a) it learns patterns (b) it prints labels (c) it charges up (d) it takes photos
  17. 17.⏩ In machine learning, which comes first: what training builds or recorded spoken words? (a) what training builds (b) recorded spoken words
  18. 18.⏩ In machine learning, which comes first: naming a new leaf or the trained program? (a) naming a new leaf (b) the trained program
  19. 19.True or false: “the trained program” is the model. (a) True (b) False
  20. 20.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) the model (b) training data (c) a prediction
  21. 21.⏩ In machine learning, which comes first: naming a new leaf or what training builds? (a) naming a new leaf (b) what training builds
  22. 22.⏩ In machine learning, which comes first: labelled fruit photos or typing a new spoken word? (a) labelled fruit photos (b) typing a new spoken word
  23. 23.⏩ In machine learning, which comes first: past weather records or the learned patterns? (a) past weather records (b) the learned patterns
  24. 24.Which of these is a prediction? (a) the trained program (b) labelled fruit photos (c) past weather records (d) flagging a new email
  25. 25.Which of these is the model? (a) tomorrow’s rain guess (b) what training builds (c) old emails marked spam (d) labelled fruit photos
  26. 26.⏩ In machine learning, which comes first: flagging a new email or what training builds? (a) flagging a new email (b) what training builds
  27. 27.⏩ In machine learning, which comes first: the trained program or typing a new spoken word? (a) the trained program (b) typing a new spoken word
  28. 28.True or false: “labelled fruit photos” is the model. (a) False (b) True
  29. 29.Which of these is training data? (a) old emails marked spam (b) flagging a new email (c) naming a new leaf (d) naming a new fruit photo
  30. 30.True or false: “past weather records” is a prediction. (a) True (b) False
  31. 31.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) training data (b) the model (c) a prediction
  32. 32.⏩ In machine learning, which comes first: the trained program or tomorrow’s rain guess? (a) the trained program (b) tomorrow’s rain guess
  33. 33.True or false: “typing a new spoken word” is the model. (a) False (b) True
  34. 34.Which of these is a prediction? (a) past weather records (b) recorded spoken words (c) the learned patterns (d) tomorrow’s rain guess
  35. 35.⏩ In machine learning, which comes first: the learned patterns or flagging a new email? (a) the learned patterns (b) flagging a new email
  36. 36.Which of these is training data? (a) what training builds (b) tomorrow’s rain guess (c) flagging a new email (d) past weather records
  37. 37.Which of these is the model? (a) old emails marked spam (b) past weather records (c) tomorrow’s rain guess (d) the trained program
  38. 38.⏩ In machine learning, which comes first: recorded spoken words or typing a new spoken word? (a) recorded spoken words (b) typing a new spoken word
  39. 39.True or false: “the trained program” is training data. (a) False (b) True
  40. 40.🔁 Training data, the model or a prediction: “flagging a new email”? (a) the model (b) training data (c) a prediction

Answer key

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

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