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AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 741 · 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: “flagging a new email” is a prediction. (a) True (b) False
  2. 2.⏩ In machine learning, which comes first: tomorrow’s rain guess or what training builds? (a) tomorrow’s rain guess (b) what training builds
  3. 3.🔁 Training data, the model or a prediction: “past weather records”? (a) a prediction (b) training data (c) the model
  4. 4.🧪 Why test a model on NEW examples? (a) to delete its data (b) to see if it works (c) to make it slower (d) to change its name
  5. 5.Which of these is the model? (a) naming a new leaf (b) 500 labelled leaf photos (c) old emails marked spam (d) the learned patterns
  6. 6.True or false: “500 labelled leaf photos” is the model. (a) False (b) True
  7. 7.Which of these is a prediction? (a) past weather records (b) the trained program (c) old emails marked spam (d) typing a new spoken word
  8. 8.Which of these is training data? (a) flagging a new email (b) the trained program (c) 500 labelled leaf photos (d) typing a new spoken word
  9. 9.🔁 Training data, the model or a prediction: “the trained program”? (a) training data (b) the model (c) a prediction
  10. 10.True or false: “labelled fruit photos” is training data. (a) True (b) False
  11. 11.📦 What happens during training? (a) it charges up (b) it prints labels (c) it learns patterns (d) it takes photos
  12. 12.True or false: “past weather records” is training data. (a) False (b) True
  13. 13.⏩ In machine learning, which comes first: the learned patterns or naming a new leaf? (a) the learned patterns (b) naming a new leaf
  14. 14.🔮 A trained model sees a new photo and says “mango”. This is… (a) a label error (b) a prediction (c) a password (d) training data
  15. 15.🔁 Training data, the model or a prediction: “what training builds”? (a) a prediction (b) the model (c) training data
  16. 16.⏩ In machine learning, which comes first: the trained program or recorded spoken words? (a) the trained program (b) recorded spoken words
  17. 17.🔁 Training data, the model or a prediction: “tomorrow’s rain guess”? (a) a prediction (b) the model (c) training data
  18. 18.⏩ In machine learning, which comes first: labelled fruit photos or tomorrow’s rain guess? (a) labelled fruit photos (b) tomorrow’s rain guess
  19. 19.True or false: “the trained program” is a prediction. (a) True (b) False
  20. 20.Which of these is training data? (a) naming a new leaf (b) the learned patterns (c) labelled fruit photos (d) what training builds
  21. 21.True or false: “labelled fruit photos” is the model. (a) False (b) True
  22. 22.⏩ In machine learning, which comes first: the trained program or past weather records? (a) the trained program (b) past weather records
  23. 23.Which of these is training data? (a) past weather records (b) the trained program (c) flagging a new email (d) naming a new fruit photo
  24. 24.Which of these is the model? (a) labelled fruit photos (b) what training builds (c) naming a new leaf (d) tomorrow’s rain guess
  25. 25.⏩ In machine learning, which comes first: past weather records or naming a new leaf? (a) past weather records (b) naming a new leaf
  26. 26.Which of these is the model? (a) recorded spoken words (b) labelled fruit photos (c) flagging a new email (d) the trained program
  27. 27.🔁 Training data, the model or a prediction: “flagging a new email”? (a) a prediction (b) the model (c) training data
  28. 28.🔁 Training data, the model or a prediction: “naming a new fruit photo”? (a) a prediction (b) the model (c) training data
  29. 29.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) the model (b) training data (c) a prediction
  30. 30.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) the model (b) a prediction (c) training data
  31. 31.True or false: “naming a new fruit photo” is training data. (a) True (b) False
  32. 32.🔁 What is the right order? (a) data, prediction, model (b) model, prediction, data (c) data, model, prediction (d) prediction, data, model
  33. 33.⏩ In machine learning, which comes first: the trained program or 500 labelled leaf photos? (a) the trained program (b) 500 labelled leaf photos
  34. 34.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) the model (b) training data (c) a prediction
  35. 35.⏩ In machine learning, which comes first: what training builds or flagging a new email? (a) what training builds (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: naming a new leaf or the learned patterns? (a) naming a new leaf (b) the learned patterns
  38. 38.True or false: “the trained program” is the model. (a) False (b) True
  39. 39.True or false: “old emails marked spam” is the model. (a) False (b) True
  40. 40.⏩ In machine learning, which comes first: what training builds or naming a new leaf? (a) what training builds (b) naming a new leaf

Answer key

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

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