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AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 489 · 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) what training builds (b) 500 labelled leaf photos (c) labelled fruit photos (d) naming a new leaf
  2. 2.Which of these is training data? (a) recorded spoken words (b) naming a new leaf (c) what training builds (d) the learned patterns
  3. 3.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) the model (b) training data (c) a prediction
  4. 4.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) the model (b) a prediction (c) training data
  5. 5.Which of these is a prediction? (a) past weather records (b) naming a new leaf (c) labelled fruit photos (d) old emails marked spam
  6. 6.🔁 Training data, the model or a prediction: “naming a new leaf”? (a) the model (b) training data (c) a prediction
  7. 7.Which of these is a prediction? (a) old emails marked spam (b) the trained program (c) typing a new spoken word (d) the learned patterns
  8. 8.🔁 What is the right order? (a) model, prediction, data (b) data, prediction, model (c) data, model, prediction (d) prediction, data, model
  9. 9.📦 What happens during training? (a) it prints labels (b) it takes photos (c) it charges up (d) it learns patterns
  10. 10.🔁 Training data, the model or a prediction: “naming a new fruit photo”? (a) training data (b) the model (c) a prediction
  11. 11.Which of these is the model? (a) typing a new spoken word (b) tomorrow’s rain guess (c) labelled fruit photos (d) the trained program
  12. 12.True or false: “the trained program” is a prediction. (a) True (b) False
  13. 13.True or false: “the trained program” is the model. (a) False (b) True
  14. 14.🔁 Training data, the model or a prediction: “flagging a new email”? (a) the model (b) training data (c) a prediction
  15. 15.⏩ In machine learning, which comes first: the learned patterns or naming a new leaf? (a) the learned patterns (b) naming a new leaf
  16. 16.True or false: “typing a new spoken word” is the model. (a) True (b) False
  17. 17.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) training data (b) the model (c) a prediction
  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.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) a prediction (b) the model (c) training data
  20. 20.🔁 Training data, the model or a prediction: “the learned patterns”? (a) a prediction (b) the model (c) training data
  21. 21.🔁 Training data, the model or a prediction: “the trained program”? (a) the model (b) a prediction (c) training data
  22. 22.True or false: “naming a new fruit photo” is a prediction. (a) True (b) False
  23. 23.⏩ In machine learning, which comes first: the learned patterns or recorded spoken words? (a) the learned patterns (b) recorded spoken words
  24. 24.⏩ In machine learning, which comes first: the trained program or tomorrow’s rain guess? (a) the trained program (b) tomorrow’s rain guess
  25. 25.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) the model (b) training data (c) a prediction
  26. 26.🔁 Training data, the model or a prediction: “what training builds”? (a) a prediction (b) the model (c) training data
  27. 27.Which of these is training data? (a) old emails marked spam (b) typing a new spoken word (c) tomorrow’s rain guess (d) the learned patterns
  28. 28.🔮 A trained model sees a new photo and says “mango”. This is… (a) a label error (b) training data (c) a password (d) a prediction
  29. 29.True or false: “naming a new leaf” is a prediction. (a) False (b) True
  30. 30.True or false: “500 labelled leaf photos” is a prediction. (a) False (b) True
  31. 31.Which of these is training data? (a) the trained program (b) flagging a new email (c) the learned patterns (d) past weather records
  32. 32.⏩ In machine learning, which comes first: flagging a new email or what training builds? (a) flagging a new email (b) what training builds
  33. 33.🔁 Training data, the model or a prediction: “past weather records”? (a) the model (b) training data (c) a prediction
  34. 34.True or false: “tomorrow’s rain guess” is training data. (a) True (b) False
  35. 35.Which of these is training data? (a) 500 labelled leaf photos (b) flagging a new email (c) naming a new leaf (d) typing a new spoken word
  36. 36.⏩ In machine learning, which comes first: what training builds or old emails marked spam? (a) what training builds (b) old emails marked spam
  37. 37.Which of these is a prediction? (a) recorded spoken words (b) the trained program (c) tomorrow’s rain guess (d) what training builds
  38. 38.True or false: “500 labelled leaf photos” is training data. (a) True (b) False
  39. 39.True or false: “naming a new fruit photo” is the model. (a) True (b) False
  40. 40.🧪 Why test a model on NEW examples? (a) to delete its data (b) to make it slower (c) to see if it works (d) to change its name

Answer key

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

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