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AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 700 · 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 the model? (a) old emails marked spam (b) the trained program (c) recorded spoken words (d) labelled fruit photos
  2. 2.🔁 Training data, the model or a prediction: “what training builds”? (a) training data (b) the model (c) a prediction
  3. 3.⏩ In machine learning, which comes first: tomorrow’s rain guess or the learned patterns? (a) tomorrow’s rain guess (b) the learned patterns
  4. 4.📦 What happens during training? (a) it charges up (b) it takes photos (c) it prints labels (d) it learns patterns
  5. 5.True or false: “flagging a new email” is a prediction. (a) False (b) True
  6. 6.Which of these is a prediction? (a) recorded spoken words (b) flagging a new email (c) labelled fruit photos (d) old emails marked spam
  7. 7.⏩ In machine learning, which comes first: naming a new leaf or the trained program? (a) naming a new leaf (b) the trained program
  8. 8.True or false: “old emails marked spam” is a prediction. (a) False (b) True
  9. 9.🔁 Training data, the model or a prediction: “naming a new fruit photo”? (a) training data (b) a prediction (c) the model
  10. 10.🔁 Training data, the model or a prediction: “past weather records”? (a) training data (b) the model (c) a prediction
  11. 11.🔁 What is the right order? (a) prediction, data, model (b) model, prediction, data (c) data, prediction, model (d) data, model, prediction
  12. 12.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) the model (b) training data (c) a prediction
  13. 13.⏩ In machine learning, which comes first: typing a new spoken word or the trained program? (a) typing a new spoken word (b) the trained program
  14. 14.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) the model (b) a prediction (c) training data
  15. 15.🔁 Training data, the model or a prediction: “the trained program”? (a) the model (b) training data (c) a prediction
  16. 16.Which of these is training data? (a) recorded spoken words (b) tomorrow’s rain guess (c) flagging a new email (d) naming a new leaf
  17. 17.True or false: “the trained program” is the model. (a) True (b) False
  18. 18.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) the model (b) a prediction (c) training data
  19. 19.Which of these is the model? (a) the learned patterns (b) recorded spoken words (c) past weather records (d) labelled fruit photos
  20. 20.🧪 Why test a model on NEW examples? (a) to change its name (b) to make it slower (c) to delete its data (d) to see if it works
  21. 21.True or false: “the learned patterns” is the model. (a) False (b) True
  22. 22.🔮 A trained model sees a new photo and says “mango”. This is… (a) training data (b) a prediction (c) a password (d) a label error
  23. 23.True or false: “naming a new fruit photo” is a prediction. (a) False (b) True
  24. 24.Which of these is a prediction? (a) typing a new spoken word (b) what training builds (c) old emails marked spam (d) labelled fruit photos
  25. 25.🔁 Training data, the model or a prediction: “flagging a new email”? (a) the model (b) a prediction (c) training data
  26. 26.True or false: “what training builds” is the model. (a) True (b) False
  27. 27.Which of these is a prediction? (a) labelled fruit photos (b) the trained program (c) recorded spoken words (d) naming a new fruit photo
  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.⏩ In machine learning, which comes first: tomorrow’s rain guess or old emails marked spam? (a) tomorrow’s rain guess (b) old emails marked spam
  30. 30.⏩ In machine learning, which comes first: the trained program or old emails marked spam? (a) the trained program (b) old emails marked spam
  31. 31.True or false: “recorded spoken words” is training data. (a) True (b) False
  32. 32.Which of these is training data? (a) tomorrow’s rain guess (b) typing a new spoken word (c) past weather records (d) flagging a new email
  33. 33.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) the model (b) a prediction (c) training data
  34. 34.⏩ In machine learning, which comes first: old emails marked spam or what training builds? (a) old emails marked spam (b) what training builds
  35. 35.🔁 Training data, the model or a prediction: “the learned patterns”? (a) a prediction (b) the model (c) training data
  36. 36.True or false: “old emails marked spam” is training data. (a) False (b) True
  37. 37.🔁 Training data, the model or a prediction: “tomorrow’s rain guess”? (a) training data (b) the model (c) a prediction
  38. 38.⏩ In machine learning, which comes first: tomorrow’s rain guess or the trained program? (a) tomorrow’s rain guess (b) the trained program
  39. 39.⏩ 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
  40. 40.🔁 Training data, the model or a prediction: “naming a new leaf”? (a) training data (b) a prediction (c) the model

Answer key

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

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