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AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 811 · 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 a prediction? (a) what training builds (b) the learned patterns (c) recorded spoken words (d) naming a new leaf
  2. 2.📦 What happens during training? (a) it prints labels (b) it learns patterns (c) it charges up (d) it takes photos
  3. 3.🔁 Training data, the model or a prediction: “naming a new fruit photo”? (a) the model (b) training data (c) a prediction
  4. 4.Which of these is the model? (a) labelled fruit photos (b) naming a new leaf (c) what training builds (d) 500 labelled leaf photos
  5. 5.True or false: “recorded spoken words” is the model. (a) True (b) False
  6. 6.True or false: “typing a new spoken word” is training data. (a) False (b) True
  7. 7.🧪 Why test a model on NEW examples? (a) to see if it works (b) to delete its data (c) to make it slower (d) to change its name
  8. 8.🔁 Training data, the model or a prediction: “naming a new leaf”? (a) training data (b) a prediction (c) the model
  9. 9.⏩ In machine learning, which comes first: 500 labelled leaf photos or tomorrow’s rain guess? (a) 500 labelled leaf photos (b) tomorrow’s rain guess
  10. 10.True or false: “the trained program” is the model. (a) False (b) True
  11. 11.Which of these is the model? (a) the trained program (b) recorded spoken words (c) labelled fruit photos (d) past weather records
  12. 12.⏩ In machine learning, which comes first: tomorrow’s rain guess or the trained program? (a) tomorrow’s rain guess (b) the trained program
  13. 13.⏩ In machine learning, which comes first: naming a new leaf or labelled fruit photos? (a) naming a new leaf (b) labelled fruit photos
  14. 14.True or false: “naming a new leaf” is training data. (a) True (b) False
  15. 15.⏩ In machine learning, which comes first: 500 labelled leaf photos or naming a new fruit photo? (a) 500 labelled leaf photos (b) naming a new fruit photo
  16. 16.Which of these is training data? (a) 500 labelled leaf photos (b) typing a new spoken word (c) tomorrow’s rain guess (d) the trained program
  17. 17.True or false: “500 labelled leaf photos” is the model. (a) False (b) True
  18. 18.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) a prediction (b) the model (c) training data
  19. 19.⏩ In machine learning, which comes first: recorded spoken words or the trained program? (a) recorded spoken words (b) the trained program
  20. 20.⏩ In machine learning, which comes first: the learned patterns or labelled fruit photos? (a) the learned patterns (b) labelled fruit photos
  21. 21.True or false: “flagging a new email” is the model. (a) True (b) False
  22. 22.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) a prediction (b) the model (c) training data
  23. 23.⏩ In machine learning, which comes first: naming a new leaf or old emails marked spam? (a) naming a new leaf (b) old emails marked spam
  24. 24.🔁 What is the right order? (a) data, prediction, model (b) prediction, data, model (c) data, model, prediction (d) model, prediction, data
  25. 25.🔮 A trained model sees a new photo and says “mango”. This is… (a) a password (b) a label error (c) training data (d) a prediction
  26. 26.⏩ 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
  27. 27.Which of these is the model? (a) 500 labelled leaf photos (b) recorded spoken words (c) old emails marked spam (d) the learned patterns
  28. 28.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) the model (b) training data (c) a prediction
  29. 29.Which of these is training data? (a) what training builds (b) tomorrow’s rain guess (c) past weather records (d) naming a new leaf
  30. 30.⏩ In machine learning, which comes first: naming a new leaf or recorded spoken words? (a) naming a new leaf (b) recorded spoken words
  31. 31.⏩ In machine learning, which comes first: the learned patterns or typing a new spoken word? (a) the learned patterns (b) typing a new spoken word
  32. 32.⏩ In machine learning, which comes first: the trained program or past weather records? (a) the trained program (b) past weather records
  33. 33.Which of these is training data? (a) tomorrow’s rain guess (b) the learned patterns (c) recorded spoken words (d) the trained program
  34. 34.⏩ In machine learning, which comes first: typing a new spoken word or the learned patterns? (a) typing a new spoken word (b) the learned patterns
  35. 35.⏩ In machine learning, which comes first: the learned patterns or past weather records? (a) the learned patterns (b) past weather records
  36. 36.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) a prediction (b) the model (c) training data
  37. 37.True or false: “recorded spoken words” is training data. (a) True (b) False
  38. 38.⏩ In machine learning, which comes first: past weather records or what training builds? (a) past weather records (b) what training builds
  39. 39.⏩ In machine learning, which comes first: what training builds or naming a new leaf? (a) what training builds (b) naming a new leaf
  40. 40.🔁 Training data, the model or a prediction: “tomorrow’s rain guess”? (a) training data (b) the model (c) a prediction

Answer key

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

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