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AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 495 · 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.🔁 Training data, the model or a prediction: “flagging a new email”? (a) training data (b) a prediction (c) the model
  2. 2.⏩ 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
  3. 3.⏩ In machine learning, which comes first: the learned patterns or flagging a new email? (a) the learned patterns (b) flagging a new email
  4. 4.📦 What happens during training? (a) it takes photos (b) it charges up (c) it prints labels (d) it learns patterns
  5. 5.⏩ In machine learning, which comes first: 500 labelled leaf photos or naming a new leaf? (a) 500 labelled leaf photos (b) naming a new leaf
  6. 6.⏩ In machine learning, which comes first: labelled fruit photos or the trained program? (a) labelled fruit photos (b) the trained program
  7. 7.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) the model (b) training data (c) a prediction
  8. 8.⏩ In machine learning, which comes first: past weather records or naming a new fruit photo? (a) past weather records (b) naming a new fruit photo
  9. 9.True or false: “labelled fruit photos” is a prediction. (a) True (b) False
  10. 10.True or false: “labelled fruit photos” is training data. (a) False (b) True
  11. 11.🔁 Training data, the model or a prediction: “the learned patterns”? (a) training data (b) a prediction (c) the model
  12. 12.⏩ 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
  13. 13.⏩ In machine learning, which comes first: what training builds or flagging a new email? (a) what training builds (b) flagging a new email
  14. 14.🔁 What is the right order? (a) data, prediction, model (b) prediction, data, model (c) model, prediction, data (d) data, model, prediction
  15. 15.Which of these is a prediction? (a) naming a new fruit photo (b) the learned patterns (c) old emails marked spam (d) recorded spoken words
  16. 16.Which of these is training data? (a) naming a new fruit photo (b) what training builds (c) past weather records (d) flagging a new email
  17. 17.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) a prediction (b) the model (c) training data
  18. 18.Which of these is the model? (a) recorded spoken words (b) the learned patterns (c) labelled fruit photos (d) flagging a new email
  19. 19.⏩ In machine learning, which comes first: past weather records or typing a new spoken word? (a) past weather records (b) typing a new spoken word
  20. 20.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) a prediction (b) training data (c) the model
  21. 21.🧪 Why test a model on NEW examples? (a) to see if it works (b) to delete its data (c) to change its name (d) to make it slower
  22. 22.True or false: “naming a new leaf” is a prediction. (a) False (b) True
  23. 23.⏩ In machine learning, which comes first: labelled fruit photos or the learned patterns? (a) labelled fruit photos (b) the learned patterns
  24. 24.Which of these is training data? (a) the trained program (b) 500 labelled leaf photos (c) typing a new spoken word (d) the learned patterns
  25. 25.True or false: “the learned patterns” is training data. (a) False (b) True
  26. 26.🔮 A trained model sees a new photo and says “mango”. This is… (a) a label error (b) training data (c) a password (d) a prediction
  27. 27.🔁 Training data, the model or a prediction: “naming a new fruit photo”? (a) the model (b) training data (c) a prediction
  28. 28.⏩ In machine learning, which comes first: what training builds or recorded spoken words? (a) what training builds (b) recorded spoken words
  29. 29.Which of these is the model? (a) labelled fruit photos (b) 500 labelled leaf photos (c) what training builds (d) naming a new fruit photo
  30. 30.🔁 Training data, the model or a prediction: “the trained program”? (a) a prediction (b) training data (c) the model
  31. 31.True or false: “naming a new fruit photo” is training data. (a) True (b) False
  32. 32.Which of these is the model? (a) typing a new spoken word (b) flagging a new email (c) the trained program (d) 500 labelled leaf photos
  33. 33.Which of these is a prediction? (a) past weather records (b) flagging a new email (c) the learned patterns (d) old emails marked spam
  34. 34.True or false: “old emails marked spam” is training data. (a) True (b) False
  35. 35.Which of these is training data? (a) what training builds (b) old emails marked spam (c) flagging a new email (d) typing a new spoken word
  36. 36.Which of these is a prediction? (a) what training builds (b) naming a new leaf (c) the trained program (d) old emails marked spam
  37. 37.True or false: “naming a new fruit photo” is a prediction. (a) False (b) True
  38. 38.⏩ 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
  39. 39.True or false: “typing a new spoken word” is training data. (a) False (b) True
  40. 40.🔁 Training data, the model or a prediction: “what training builds”? (a) the model (b) a prediction (c) training data

Answer key

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

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