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AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 678 · 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.🧪 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
  2. 2.⏩ 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
  3. 3.⏩ In machine learning, which comes first: what training builds or typing a new spoken word? (a) what training builds (b) typing a new spoken word
  4. 4.True or false: “old emails marked spam” is training data. (a) True (b) False
  5. 5.🔁 Training data, the model or a prediction: “what training builds”? (a) training data (b) a prediction (c) the model
  6. 6.⏩ In machine learning, which comes first: typing a new spoken word or labelled fruit photos? (a) typing a new spoken word (b) labelled fruit photos
  7. 7.Which of these is training data? (a) old emails marked spam (b) naming a new leaf (c) the trained program (d) what training builds
  8. 8.⏩ In machine learning, which comes first: old emails marked spam or tomorrow’s rain guess? (a) old emails marked spam (b) tomorrow’s rain guess
  9. 9.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) the model (b) a prediction (c) training data
  10. 10.Which of these is the model? (a) tomorrow’s rain guess (b) flagging a new email (c) the trained program (d) old emails marked spam
  11. 11.True or false: “the learned patterns” is a prediction. (a) True (b) False
  12. 12.🔁 Training data, the model or a prediction: “naming a new fruit photo”? (a) a prediction (b) the model (c) training data
  13. 13.Which of these is a prediction? (a) the trained program (b) old emails marked spam (c) tomorrow’s rain guess (d) 500 labelled leaf photos
  14. 14.🔮 A trained model sees a new photo and says “mango”. This is… (a) a prediction (b) a label error (c) a password (d) training data
  15. 15.Which of these is training data? (a) typing a new spoken word (b) flagging a new email (c) what training builds (d) 500 labelled leaf photos
  16. 16.Which of these is the model? (a) 500 labelled leaf photos (b) labelled fruit photos (c) flagging a new email (d) what training builds
  17. 17.True or false: “500 labelled leaf photos” is the model. (a) False (b) True
  18. 18.📦 What happens during training? (a) it learns patterns (b) it takes photos (c) it charges up (d) it prints labels
  19. 19.True or false: “the trained program” is the model. (a) False (b) True
  20. 20.⏩ In machine learning, which comes first: recorded spoken words or what training builds? (a) recorded spoken words (b) what training builds
  21. 21.Which of these is a prediction? (a) naming a new leaf (b) recorded spoken words (c) past weather records (d) old emails marked spam
  22. 22.🔁 What is the right order? (a) prediction, data, model (b) model, prediction, data (c) data, model, prediction (d) data, prediction, model
  23. 23.⏩ In machine learning, which comes first: what training builds or tomorrow’s rain guess? (a) what training builds (b) tomorrow’s rain guess
  24. 24.True or false: “naming a new fruit photo” is a prediction. (a) True (b) False
  25. 25.⏩ In machine learning, which comes first: the trained program or 500 labelled leaf photos? (a) the trained program (b) 500 labelled leaf photos
  26. 26.🔁 Training data, the model or a prediction: “naming a new leaf”? (a) the model (b) training data (c) a prediction
  27. 27.True or false: “what training builds” is the model. (a) False (b) True
  28. 28.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) the model (b) training data (c) a prediction
  29. 29.Which of these is the model? (a) tomorrow’s rain guess (b) old emails marked spam (c) naming a new leaf (d) the learned patterns
  30. 30.⏩ In machine learning, which comes first: naming a new fruit photo or the trained program? (a) naming a new fruit photo (b) the trained program
  31. 31.True or false: “the learned patterns” is training data. (a) True (b) False
  32. 32.True or false: “the trained program” is a prediction. (a) True (b) False
  33. 33.Which of these is training data? (a) past weather records (b) the trained program (c) naming a new fruit photo (d) the learned patterns
  34. 34.⏩ 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
  35. 35.⏩ In machine learning, which comes first: old emails marked spam or flagging a new email? (a) old emails marked spam (b) flagging a new email
  36. 36.True or false: “recorded spoken words” is training data. (a) False (b) True
  37. 37.⏩ In machine learning, which comes first: the learned patterns or past weather records? (a) the learned patterns (b) past weather records
  38. 38.True or false: “typing a new spoken word” is the model. (a) True (b) False
  39. 39.⏩ In machine learning, which comes first: tomorrow’s rain guess or what training builds? (a) tomorrow’s rain guess (b) what training builds
  40. 40.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) training data (b) a prediction (c) the model

Answer key

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

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