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AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 704 · 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.🧪 Why test a model on NEW examples? (a) to delete its data (b) to change its name (c) to see if it works (d) to make it slower
  2. 2.📦 What happens during training? (a) it charges up (b) it prints labels (c) it learns patterns (d) it takes photos
  3. 3.Which of these is a prediction? (a) past weather records (b) tomorrow’s rain guess (c) 500 labelled leaf photos (d) old emails marked spam
  4. 4.⏩ In machine learning, which comes first: recorded spoken words or typing a new spoken word? (a) recorded spoken words (b) typing a new spoken word
  5. 5.⏩ 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
  6. 6.Which of these is the model? (a) flagging a new email (b) naming a new leaf (c) the trained program (d) past weather records
  7. 7.⏩ 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
  8. 8.True or false: “old emails marked spam” is the model. (a) False (b) True
  9. 9.True or false: “what training builds” is training data. (a) False (b) True
  10. 10.⏩ In machine learning, which comes first: the trained program or old emails marked spam? (a) the trained program (b) old emails marked spam
  11. 11.⏩ In machine learning, which comes first: flagging a new email or the trained program? (a) flagging a new email (b) the trained program
  12. 12.True or false: “naming a new fruit photo” is a prediction. (a) True (b) False
  13. 13.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) training data (b) the model (c) a prediction
  14. 14.Which of these is training data? (a) tomorrow’s rain guess (b) the learned patterns (c) labelled fruit photos (d) naming a new leaf
  15. 15.🔁 What is the right order? (a) data, prediction, model (b) data, model, prediction (c) model, prediction, data (d) prediction, data, model
  16. 16.🔁 Training data, the model or a prediction: “naming a new fruit photo”? (a) training data (b) the model (c) a prediction
  17. 17.Which of these is the model? (a) flagging a new email (b) the learned patterns (c) recorded spoken words (d) labelled fruit photos
  18. 18.⏩ In machine learning, which comes first: naming a new leaf or what training builds? (a) naming a new leaf (b) what training builds
  19. 19.True or false: “typing a new spoken word” is a prediction. (a) False (b) True
  20. 20.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) a prediction (b) training data (c) the model
  21. 21.True or false: “naming a new fruit photo” is the model. (a) True (b) False
  22. 22.🔁 Training data, the model or a prediction: “flagging a new email”? (a) the model (b) training data (c) a prediction
  23. 23.⏩ In machine learning, which comes first: the trained program or typing a new spoken word? (a) the trained program (b) typing a new spoken word
  24. 24.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) training data (b) a prediction (c) the model
  25. 25.🔁 Training data, the model or a prediction: “what training builds”? (a) the model (b) a prediction (c) training data
  26. 26.Which of these is training data? (a) the trained program (b) typing a new spoken word (c) old emails marked spam (d) naming a new fruit photo
  27. 27.Which of these is the model? (a) labelled fruit photos (b) what training builds (c) naming a new leaf (d) past weather records
  28. 28.⏩ In machine learning, which comes first: typing a new spoken word or past weather records? (a) typing a new spoken word (b) past weather records
  29. 29.🔮 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
  30. 30.🔁 Training data, the model or a prediction: “past weather records”? (a) training data (b) a prediction (c) the model
  31. 31.🔁 Training data, the model or a prediction: “the trained program”? (a) a prediction (b) the model (c) training data
  32. 32.True or false: “flagging a new email” is a prediction. (a) True (b) False
  33. 33.⏩ In machine learning, which comes first: what training builds or past weather records? (a) what training builds (b) past weather records
  34. 34.⏩ In machine learning, which comes first: the trained program or tomorrow’s rain guess? (a) the trained program (b) tomorrow’s rain guess
  35. 35.🔁 Training data, the model or a prediction: “tomorrow’s rain guess”? (a) training data (b) a prediction (c) the model
  36. 36.True or false: “tomorrow’s rain guess” is a prediction. (a) True (b) False
  37. 37.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) training data (b) the model (c) a prediction
  38. 38.True or false: “labelled fruit photos” is the model. (a) True (b) False
  39. 39.⏩ In machine learning, which comes first: recorded spoken words or the trained program? (a) recorded spoken words (b) the trained program
  40. 40.⏩ In machine learning, which comes first: old emails marked spam or what training builds? (a) old emails marked spam (b) what training builds

Answer key

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

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