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AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 921 · 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 training data? (a) naming a new leaf (b) past weather records (c) the learned patterns (d) typing a new spoken word
  2. 2.Which of these is training data? (a) the learned patterns (b) naming a new fruit photo (c) tomorrow’s rain guess (d) labelled fruit photos
  3. 3.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) the model (b) training data (c) a prediction
  4. 4.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) training data (b) a prediction (c) the model
  5. 5.🔁 Training data, the model or a prediction: “what training builds”? (a) the model (b) a prediction (c) training data
  6. 6.Which of these is training data? (a) 500 labelled leaf photos (b) what training builds (c) the trained program (d) naming a new fruit photo
  7. 7.Which of these is a prediction? (a) past weather records (b) tomorrow’s rain guess (c) 500 labelled leaf photos (d) recorded spoken words
  8. 8.⏩ In machine learning, which comes first: the trained program or past weather records? (a) the trained program (b) past weather records
  9. 9.Which of these is the model? (a) labelled fruit photos (b) 500 labelled leaf photos (c) the learned patterns (d) tomorrow’s rain guess
  10. 10.🔁 Training data, the model or a prediction: “past weather records”? (a) a prediction (b) training data (c) the model
  11. 11.🔁 Training data, the model or a prediction: “tomorrow’s rain guess”? (a) training data (b) a prediction (c) the model
  12. 12.⏩ In machine learning, which comes first: naming a new leaf or what training builds? (a) naming a new leaf (b) what training builds
  13. 13.📦 What happens during training? (a) it charges up (b) it takes photos (c) it learns patterns (d) it prints labels
  14. 14.Which of these is training data? (a) tomorrow’s rain guess (b) old emails marked spam (c) typing a new spoken word (d) what training builds
  15. 15.True or false: “the learned patterns” is the model. (a) True (b) False
  16. 16.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) the model (b) a prediction (c) training data
  17. 17.True or false: “naming a new fruit photo” is the model. (a) True (b) False
  18. 18.True or false: “recorded spoken words” is a prediction. (a) False (b) True
  19. 19.🧪 Why test a model on NEW examples? (a) to see if it works (b) to delete its data (c) to make it slower (d) to change its name
  20. 20.Which of these is a prediction? (a) old emails marked spam (b) past weather records (c) naming a new leaf (d) the trained program
  21. 21.True or false: “old emails marked spam” is the model. (a) True (b) False
  22. 22.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) the model (b) a prediction (c) training data
  23. 23.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) a prediction (b) the model (c) training data
  24. 24.🔮 A trained model sees a new photo and says “mango”. This is… (a) a password (b) training data (c) a label error (d) a prediction
  25. 25.Which of these is training data? (a) typing a new spoken word (b) flagging a new email (c) the trained program (d) recorded spoken words
  26. 26.⏩ In machine learning, which comes first: what training builds or past weather records? (a) what training builds (b) past weather records
  27. 27.True or false: “the trained program” is training data. (a) False (b) True
  28. 28.⏩ 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
  29. 29.⏩ In machine learning, which comes first: the learned patterns or tomorrow’s rain guess? (a) the learned patterns (b) tomorrow’s rain guess
  30. 30.Which of these is a prediction? (a) flagging a new email (b) recorded spoken words (c) labelled fruit photos (d) past weather records
  31. 31.🔁 What is the right order? (a) prediction, data, model (b) data, prediction, model (c) data, model, prediction (d) model, prediction, data
  32. 32.🔁 Training data, the model or a prediction: “flagging a new email”? (a) training data (b) a prediction (c) the model
  33. 33.True or false: “tomorrow’s rain guess” is the model. (a) True (b) False
  34. 34.🔁 Training data, the model or a prediction: “naming a new leaf”? (a) a prediction (b) the model (c) training data
  35. 35.🔁 Training data, the model or a prediction: “the learned patterns”? (a) the model (b) training data (c) a prediction
  36. 36.True or false: “the learned patterns” is a prediction. (a) True (b) False
  37. 37.⏩ In machine learning, which comes first: the learned patterns or naming a new leaf? (a) the learned patterns (b) naming a new leaf
  38. 38.⏩ 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
  39. 39.🔁 Training data, the model or a prediction: “the trained program”? (a) training data (b) the model (c) a prediction
  40. 40.Which of these is a prediction? (a) old emails marked spam (b) the trained program (c) naming a new fruit photo (d) 500 labelled leaf photos

Answer key

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

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