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AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 85 · 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.True or false: “the trained program” is a prediction. (a) True (b) False
  2. 2.Which of these is the model? (a) old emails marked spam (b) the trained program (c) naming a new leaf (d) flagging a new email
  3. 3.🧪 Why test a model on NEW examples? (a) to make it slower (b) to see if it works (c) to change its name (d) to delete its data
  4. 4.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) training data (b) the model (c) a prediction
  5. 5.⏩ In machine learning, which comes first: tomorrow’s rain guess or recorded spoken words? (a) tomorrow’s rain guess (b) recorded spoken words
  6. 6.Which of these is training data? (a) 500 labelled leaf photos (b) typing a new spoken word (c) flagging a new email (d) tomorrow’s rain guess
  7. 7.📦 What happens during training? (a) it prints labels (b) it charges up (c) it takes photos (d) it learns patterns
  8. 8.True or false: “typing a new spoken word” is a prediction. (a) True (b) False
  9. 9.⏩ 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
  10. 10.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) a prediction (b) training data (c) the model
  11. 11.Which of these is a prediction? (a) old emails marked spam (b) past weather records (c) tomorrow’s rain guess (d) recorded spoken words
  12. 12.🔁 Training data, the model or a prediction: “past weather records”? (a) the model (b) a prediction (c) training data
  13. 13.⏩ In machine learning, which comes first: old emails marked spam or the learned patterns? (a) old emails marked spam (b) the learned patterns
  14. 14.Which of these is the model? (a) typing a new spoken word (b) flagging a new email (c) naming a new leaf (d) the learned patterns
  15. 15.True or false: “the learned patterns” is training data. (a) True (b) False
  16. 16.True or false: “labelled fruit photos” is a prediction. (a) True (b) False
  17. 17.🔁 What is the right order? (a) prediction, data, model (b) model, prediction, data (c) data, prediction, model (d) data, model, prediction
  18. 18.True or false: “old emails marked spam” is the model. (a) False (b) True
  19. 19.True or false: “500 labelled leaf photos” is a prediction. (a) False (b) True
  20. 20.🔁 Training data, the model or a prediction: “naming a new fruit photo”? (a) training data (b) the model (c) a prediction
  21. 21.⏩ In machine learning, which comes first: flagging a new email or past weather records? (a) flagging a new email (b) past weather records
  22. 22.⏩ In machine learning, which comes first: recorded spoken words or naming a new fruit photo? (a) recorded spoken words (b) naming a new fruit photo
  23. 23.Which of these is a prediction? (a) naming a new leaf (b) past weather records (c) the trained program (d) recorded spoken words
  24. 24.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) a prediction (b) the model (c) training data
  25. 25.🔁 Training data, the model or a prediction: “what training builds”? (a) a prediction (b) training data (c) the model
  26. 26.⏩ In machine learning, which comes first: the trained program or flagging a new email? (a) the trained program (b) flagging a new email
  27. 27.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) training data (b) the model (c) a prediction
  28. 28.Which of these is training data? (a) flagging a new email (b) typing a new spoken word (c) recorded spoken words (d) the learned patterns
  29. 29.True or false: “the learned patterns” is the model. (a) True (b) False
  30. 30.⏩ In machine learning, which comes first: the learned patterns or tomorrow’s rain guess? (a) the learned patterns (b) tomorrow’s rain guess
  31. 31.⏩ In machine learning, which comes first: the learned patterns or past weather records? (a) the learned patterns (b) past weather records
  32. 32.🔮 A trained model sees a new photo and says “mango”. This is… (a) a label error (b) a password (c) a prediction (d) training data
  33. 33.True or false: “old emails marked spam” is training data. (a) True (b) False
  34. 34.🔁 Training data, the model or a prediction: “flagging a new email”? (a) training data (b) a prediction (c) the model
  35. 35.True or false: “the trained program” is the model. (a) True (b) False
  36. 36.⏩ In machine learning, which comes first: what training builds or naming a new leaf? (a) what training builds (b) naming a new leaf
  37. 37.Which of these is a prediction? (a) recorded spoken words (b) flagging a new email (c) labelled fruit photos (d) 500 labelled leaf photos
  38. 38.Which of these is a prediction? (a) 500 labelled leaf photos (b) recorded spoken words (c) naming a new fruit photo (d) past weather records
  39. 39.True or false: “flagging a new email” is the model. (a) False (b) True
  40. 40.⏩ 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

Answer key

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

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