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AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 949 · 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.True or false: “recorded spoken words” is the model. (a) False (b) True
  2. 2.Which of these is training data? (a) what training builds (b) 500 labelled leaf photos (c) naming a new fruit photo (d) flagging a new email
  3. 3.Which of these is a prediction? (a) past weather records (b) the learned patterns (c) typing a new spoken word (d) what training builds
  4. 4.Which of these is the model? (a) tomorrow’s rain guess (b) typing a new spoken word (c) the learned patterns (d) recorded spoken words
  5. 5.📦 What happens during training? (a) it prints labels (b) it takes photos (c) it learns patterns (d) it charges up
  6. 6.🔁 What is the right order? (a) data, model, prediction (b) data, prediction, model (c) model, prediction, data (d) prediction, data, model
  7. 7.🔮 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
  8. 8.True or false: “recorded spoken words” is training data. (a) True (b) False
  9. 9.True or false: “the trained program” is the model. (a) True (b) False
  10. 10.True or false: “what training builds” is training data. (a) False (b) True
  11. 11.True or false: “the learned patterns” is training data. (a) True (b) False
  12. 12.🔁 Training data, the model or a prediction: “naming a new fruit photo”? (a) training data (b) a prediction (c) the model
  13. 13.Which of these is the model? (a) what training builds (b) labelled fruit photos (c) naming a new fruit photo (d) recorded spoken words
  14. 14.🔁 Training data, the model or a prediction: “what training builds”? (a) the model (b) a prediction (c) training data
  15. 15.⏩ In machine learning, which comes first: naming a new fruit photo or the learned patterns? (a) naming a new fruit photo (b) the learned patterns
  16. 16.⏩ 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
  17. 17.Which of these is a prediction? (a) flagging a new email (b) old emails marked spam (c) 500 labelled leaf photos (d) the learned patterns
  18. 18.🔁 Training data, the model or a prediction: “flagging a new email”? (a) the model (b) training data (c) a prediction
  19. 19.⏩ In machine learning, which comes first: old emails marked spam or the trained program? (a) old emails marked spam (b) the trained program
  20. 20.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) the model (b) training data (c) a prediction
  21. 21.🔁 Training data, the model or a prediction: “the trained program”? (a) training data (b) a prediction (c) the model
  22. 22.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) a prediction (b) the model (c) training data
  23. 23.⏩ In machine learning, which comes first: what training builds or naming a new leaf? (a) what training builds (b) naming a new leaf
  24. 24.⏩ 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
  25. 25.🧪 Why test a model on NEW examples? (a) to delete its data (b) to change its name (c) to make it slower (d) to see if it works
  26. 26.⏩ 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
  27. 27.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) the model (b) a prediction (c) training data
  28. 28.Which of these is training data? (a) naming a new leaf (b) typing a new spoken word (c) naming a new fruit photo (d) past weather records
  29. 29.⏩ In machine learning, which comes first: the trained program or flagging a new email? (a) the trained program (b) flagging a new email
  30. 30.Which of these is training data? (a) typing a new spoken word (b) naming a new fruit photo (c) recorded spoken words (d) naming a new leaf
  31. 31.🔁 Training data, the model or a prediction: “the learned patterns”? (a) training data (b) a prediction (c) the model
  32. 32.⏩ 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
  33. 33.🔁 Training data, the model or a prediction: “naming a new leaf”? (a) the model (b) training data (c) a prediction
  34. 34.True or false: “old emails marked spam” is training data. (a) True (b) False
  35. 35.⏩ In machine learning, which comes first: past weather records or tomorrow’s rain guess? (a) past weather records (b) tomorrow’s rain guess
  36. 36.⏩ In machine learning, which comes first: naming a new leaf or the trained program? (a) naming a new leaf (b) the trained program
  37. 37.⏩ In machine learning, which comes first: the learned patterns or 500 labelled leaf photos? (a) the learned patterns (b) 500 labelled leaf photos
  38. 38.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) training data (b) a prediction (c) the model
  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.True or false: “old emails marked spam” is a prediction. (a) False (b) True

Answer key

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

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