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AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 526 · 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) typing a new spoken word (b) naming a new fruit photo (c) labelled fruit photos (d) the learned patterns
  2. 2.📦 What happens during training? (a) it learns patterns (b) it takes photos (c) it prints labels (d) it charges up
  3. 3.True or false: “what training builds” is the model. (a) False (b) True
  4. 4.Which of these is a prediction? (a) what training builds (b) recorded spoken words (c) the learned patterns (d) flagging a new email
  5. 5.Which of these is a prediction? (a) 500 labelled leaf photos (b) old emails marked spam (c) naming a new leaf (d) what training builds
  6. 6.True or false: “past weather records” is training data. (a) True (b) False
  7. 7.True or false: “500 labelled leaf photos” is a prediction. (a) False (b) True
  8. 8.Which of these is training data? (a) recorded spoken words (b) the trained program (c) naming a new fruit photo (d) the learned patterns
  9. 9.🔁 Training data, the model or a prediction: “tomorrow’s rain guess”? (a) a prediction (b) the model (c) training data
  10. 10.⏩ In machine learning, which comes first: the learned patterns or past weather records? (a) the learned patterns (b) past weather records
  11. 11.🔁 Training data, the model or a prediction: “naming a new leaf”? (a) training data (b) the model (c) a prediction
  12. 12.🔮 A trained model sees a new photo and says “mango”. This is… (a) a label error (b) a prediction (c) training data (d) a password
  13. 13.🔁 Training data, the model or a prediction: “naming a new fruit photo”? (a) the model (b) training data (c) a prediction
  14. 14.⏩ In machine learning, which comes first: tomorrow’s rain guess or the learned patterns? (a) tomorrow’s rain guess (b) the learned patterns
  15. 15.Which of these is the model? (a) labelled fruit photos (b) what training builds (c) recorded spoken words (d) past weather records
  16. 16.Which of these is a prediction? (a) what training builds (b) labelled fruit photos (c) typing a new spoken word (d) recorded spoken words
  17. 17.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) a prediction (b) training data (c) the model
  18. 18.⏩ In machine learning, which comes first: recorded spoken words or the learned patterns? (a) recorded spoken words (b) the learned patterns
  19. 19.True or false: “old emails marked spam” is training data. (a) False (b) True
  20. 20.Which of these is training data? (a) tomorrow’s rain guess (b) old emails marked spam (c) what training builds (d) the learned patterns
  21. 21.🔁 What is the right order? (a) model, prediction, data (b) data, model, prediction (c) data, prediction, model (d) prediction, data, model
  22. 22.⏩ 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
  23. 23.🔁 Training data, the model or a prediction: “flagging a new email”? (a) a prediction (b) training data (c) the model
  24. 24.Which of these is training data? (a) typing a new spoken word (b) labelled fruit photos (c) flagging a new email (d) the learned patterns
  25. 25.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) a prediction (b) the model (c) training data
  26. 26.🔁 Training data, the model or a prediction: “the learned patterns”? (a) the model (b) a prediction (c) training data
  27. 27.Which of these is training data? (a) what training builds (b) naming a new leaf (c) 500 labelled leaf photos (d) typing a new spoken word
  28. 28.🧪 Why test a model on NEW examples? (a) to change its name (b) to delete its data (c) to make it slower (d) to see if it works
  29. 29.⏩ In machine learning, which comes first: 500 labelled leaf photos or typing a new spoken word? (a) 500 labelled leaf photos (b) typing a new spoken word
  30. 30.🔁 Training data, the model or a prediction: “past weather records”? (a) the model (b) a prediction (c) training data
  31. 31.True or false: “labelled fruit photos” is the model. (a) False (b) True
  32. 32.True or false: “tomorrow’s rain guess” is a prediction. (a) False (b) True
  33. 33.True or false: “typing a new spoken word” is a prediction. (a) False (b) True
  34. 34.Which of these is the model? (a) typing a new spoken word (b) naming a new fruit photo (c) the trained program (d) old emails marked spam
  35. 35.⏩ In machine learning, which comes first: the trained program or tomorrow’s rain guess? (a) the trained program (b) tomorrow’s rain guess
  36. 36.True or false: “500 labelled leaf photos” is the model. (a) True (b) False
  37. 37.🔁 Training data, the model or a prediction: “what training builds”? (a) a prediction (b) training data (c) the model
  38. 38.⏩ In machine learning, which comes first: what training builds or flagging a new email? (a) what training builds (b) flagging a new email
  39. 39.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) training data (b) a prediction (c) the model
  40. 40.True or false: “the learned patterns” is training data. (a) False (b) True

Answer key

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

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