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AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 882 · 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: “the trained program”? (a) the model (b) a prediction (c) training data
  2. 2.⏩ 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
  3. 3.Which of these is training data? (a) the trained program (b) recorded spoken words (c) typing a new spoken word (d) naming a new leaf
  4. 4.Which of these is the model? (a) typing a new spoken word (b) the trained program (c) flagging a new email (d) tomorrow’s rain guess
  5. 5.🔁 Training data, the model or a prediction: “tomorrow’s rain guess”? (a) training data (b) the model (c) a prediction
  6. 6.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) the model (b) a prediction (c) training data
  7. 7.🔁 Training data, the model or a prediction: “the learned patterns”? (a) the model (b) a prediction (c) training data
  8. 8.🔮 A trained model sees a new photo and says “mango”. This is… (a) a prediction (b) a password (c) training data (d) a label error
  9. 9.🧪 Why test a model on NEW examples? (a) to delete its data (b) to make it slower (c) to change its name (d) to see if it works
  10. 10.True or false: “tomorrow’s rain guess” is a prediction. (a) False (b) True
  11. 11.⏩ In machine learning, which comes first: typing a new spoken word or what training builds? (a) typing a new spoken word (b) what training builds
  12. 12.📦 What happens during training? (a) it learns patterns (b) it prints labels (c) it takes photos (d) it charges up
  13. 13.🔁 What is the right order? (a) data, prediction, model (b) model, prediction, data (c) data, model, prediction (d) prediction, data, model
  14. 14.True or false: “tomorrow’s rain guess” is training data. (a) True (b) False
  15. 15.Which of these is a prediction? (a) the trained program (b) naming a new fruit photo (c) past weather records (d) recorded spoken words
  16. 16.Which of these is a prediction? (a) 500 labelled leaf photos (b) past weather records (c) old emails marked spam (d) tomorrow’s rain guess
  17. 17.⏩ In machine learning, which comes first: past weather records or the learned patterns? (a) past weather records (b) the learned patterns
  18. 18.True or false: “recorded spoken words” is a prediction. (a) False (b) True
  19. 19.🔁 Training data, the model or a prediction: “flagging a new email”? (a) the model (b) training data (c) a prediction
  20. 20.True or false: “tomorrow’s rain guess” is the model. (a) False (b) True
  21. 21.⏩ 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
  22. 22.🔁 Training data, the model or a prediction: “naming a new leaf”? (a) training data (b) a prediction (c) the model
  23. 23.🔁 Training data, the model or a prediction: “past weather records”? (a) training data (b) the model (c) a prediction
  24. 24.🔁 Training data, the model or a prediction: “naming a new fruit photo”? (a) a prediction (b) training data (c) the model
  25. 25.True or false: “the learned patterns” is the model. (a) True (b) False
  26. 26.⏩ In machine learning, which comes first: flagging a new email or what training builds? (a) flagging a new email (b) what training builds
  27. 27.True or false: “what training builds” is the model. (a) True (b) False
  28. 28.⏩ In machine learning, which comes first: the learned patterns or 500 labelled leaf photos? (a) the learned patterns (b) 500 labelled leaf photos
  29. 29.Which of these is training data? (a) old emails marked spam (b) the learned patterns (c) the trained program (d) naming a new fruit photo
  30. 30.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) training data (b) a prediction (c) the model
  31. 31.⏩ In machine learning, which comes first: labelled fruit photos or naming a new leaf? (a) labelled fruit photos (b) naming a new leaf
  32. 32.Which of these is training data? (a) flagging a new email (b) what training builds (c) naming a new fruit photo (d) past weather records
  33. 33.Which of these is the model? (a) past weather records (b) flagging a new email (c) the learned patterns (d) labelled fruit photos
  34. 34.True or false: “naming a new leaf” is a prediction. (a) True (b) False
  35. 35.True or false: “typing a new spoken word” is the model. (a) True (b) False
  36. 36.⏩ In machine learning, which comes first: tomorrow’s rain guess or past weather records? (a) tomorrow’s rain guess (b) past weather records
  37. 37.Which of these is training data? (a) the learned patterns (b) 500 labelled leaf photos (c) naming a new fruit photo (d) flagging a new email
  38. 38.True or false: “naming a new leaf” is the model. (a) False (b) True
  39. 39.🔁 Training data, the model or a prediction: “what training builds”? (a) the model (b) training data (c) a prediction
  40. 40.⏩ 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

Answer key

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

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