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AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 549 · 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 leaf”? (a) training data (b) a prediction (c) the model
  2. 2.Which of these is a prediction? (a) the learned patterns (b) old emails marked spam (c) typing a new spoken word (d) labelled fruit photos
  3. 3.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) the model (b) a prediction (c) training data
  4. 4.Which of these is training data? (a) naming a new leaf (b) the learned patterns (c) the trained program (d) past weather records
  5. 5.🔁 Training data, the model or a prediction: “past weather records”? (a) training data (b) the model (c) a prediction
  6. 6.True or false: “recorded spoken words” is training data. (a) True (b) False
  7. 7.Which of these is a prediction? (a) the trained program (b) the learned patterns (c) recorded spoken words (d) flagging a new email
  8. 8.Which of these is the model? (a) 500 labelled leaf photos (b) flagging a new email (c) the trained program (d) naming a new leaf
  9. 9.⏩ In machine learning, which comes first: flagging a new email or labelled fruit photos? (a) flagging a new email (b) labelled fruit photos
  10. 10.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) the model (b) a prediction (c) training data
  11. 11.🔁 What is the right order? (a) data, model, prediction (b) data, prediction, model (c) model, prediction, data (d) prediction, data, model
  12. 12.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) training data (b) the model (c) a prediction
  13. 13.Which of these is training data? (a) labelled fruit photos (b) the trained program (c) typing a new spoken word (d) what training builds
  14. 14.🔁 Training data, the model or a prediction: “what training builds”? (a) the model (b) a prediction (c) training data
  15. 15.Which of these is training data? (a) typing a new spoken word (b) recorded spoken words (c) the trained program (d) what training builds
  16. 16.🔁 Training data, the model or a prediction: “tomorrow’s rain guess”? (a) the model (b) training data (c) a prediction
  17. 17.True or false: “flagging a new email” is the model. (a) True (b) False
  18. 18.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) a prediction (b) the model (c) training data
  19. 19.🔁 Training data, the model or a prediction: “the trained program”? (a) the model (b) a prediction (c) training data
  20. 20.⏩ In machine learning, which comes first: what training builds or naming a new leaf? (a) what training builds (b) naming a new leaf
  21. 21.⏩ In machine learning, which comes first: past weather records or the learned patterns? (a) past weather records (b) the learned patterns
  22. 22.📦 What happens during training? (a) it charges up (b) it prints labels (c) it takes photos (d) it learns patterns
  23. 23.🔮 A trained model sees a new photo and says “mango”. This is… (a) a label error (b) training data (c) a prediction (d) a password
  24. 24.True or false: “old emails marked spam” is the model. (a) True (b) False
  25. 25.Which of these is the model? (a) what training builds (b) typing a new spoken word (c) labelled fruit photos (d) naming a new leaf
  26. 26.⏩ In machine learning, which comes first: the learned patterns or tomorrow’s rain guess? (a) the learned patterns (b) tomorrow’s rain guess
  27. 27.⏩ In machine learning, which comes first: recorded spoken words or what training builds? (a) recorded spoken words (b) what training builds
  28. 28.True or false: “old emails marked spam” is training data. (a) True (b) False
  29. 29.⏩ In machine learning, which comes first: past weather records or typing a new spoken word? (a) past weather records (b) typing a new spoken word
  30. 30.⏩ In machine learning, which comes first: old emails marked spam or what training builds? (a) old emails marked spam (b) what training builds
  31. 31.🔁 Training data, the model or a prediction: “the learned patterns”? (a) a prediction (b) training data (c) the model
  32. 32.⏩ In machine learning, which comes first: labelled fruit photos or what training builds? (a) labelled fruit photos (b) what training builds
  33. 33.Which of these is a prediction? (a) what training builds (b) naming a new fruit photo (c) the learned patterns (d) 500 labelled leaf photos
  34. 34.⏩ 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
  35. 35.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) a prediction (b) the model (c) training data
  36. 36.⏩ In machine learning, which comes first: naming a new leaf or the learned patterns? (a) naming a new leaf (b) the learned patterns
  37. 37.🧪 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
  38. 38.⏩ In machine learning, which comes first: typing a new spoken word or 500 labelled leaf photos? (a) typing a new spoken word (b) 500 labelled leaf photos
  39. 39.⏩ In machine learning, which comes first: the learned patterns or naming a new leaf? (a) the learned patterns (b) naming a new leaf
  40. 40.Which of these is training data? (a) naming a new fruit photo (b) tomorrow’s rain guess (c) the learned patterns (d) 500 labelled leaf photos

Answer key

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

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