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AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 750 · 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 a prediction? (a) the learned patterns (b) tomorrow’s rain guess (c) what training builds (d) recorded spoken words
  2. 2.🔁 Training data, the model or a prediction: “flagging a new email”? (a) a prediction (b) training data (c) the model
  3. 3.Which of these is the model? (a) 500 labelled leaf photos (b) flagging a new email (c) the learned patterns (d) naming a new fruit photo
  4. 4.Which of these is training data? (a) 500 labelled leaf photos (b) tomorrow’s rain guess (c) flagging a new email (d) typing a new spoken word
  5. 5.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) a prediction (b) the model (c) training data
  6. 6.⏩ In machine learning, which comes first: what training builds or past weather records? (a) what training builds (b) past weather records
  7. 7.⏩ In machine learning, which comes first: the learned patterns or 500 labelled leaf photos? (a) the learned patterns (b) 500 labelled leaf photos
  8. 8.🧪 Why test a model on NEW examples? (a) to change its name (b) to see if it works (c) to make it slower (d) to delete its data
  9. 9.⏩ In machine learning, which comes first: what training builds or recorded spoken words? (a) what training builds (b) recorded spoken words
  10. 10.⏩ 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
  11. 11.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) a prediction (b) training data (c) the model
  12. 12.Which of these is a prediction? (a) past weather records (b) labelled fruit photos (c) recorded spoken words (d) typing a new spoken word
  13. 13.🔁 Training data, the model or a prediction: “what training builds”? (a) a prediction (b) training data (c) the model
  14. 14.🔁 What is the right order? (a) data, model, prediction (b) prediction, data, model (c) model, prediction, data (d) data, prediction, model
  15. 15.Which of these is the model? (a) the trained program (b) naming a new leaf (c) flagging a new email (d) past weather records
  16. 16.🔮 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
  17. 17.True or false: “past weather records” is training data. (a) True (b) False
  18. 18.True or false: “recorded spoken words” is training data. (a) False (b) True
  19. 19.True or false: “500 labelled leaf photos” is training data. (a) True (b) False
  20. 20.True or false: “the trained program” is the model. (a) True (b) False
  21. 21.Which of these is training data? (a) flagging a new email (b) what training builds (c) the learned patterns (d) old emails marked spam
  22. 22.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) training data (b) the model (c) a prediction
  23. 23.🔁 Training data, the model or a prediction: “tomorrow’s rain guess”? (a) the model (b) a prediction (c) training data
  24. 24.⏩ In machine learning, which comes first: flagging a new email or what training builds? (a) flagging a new email (b) what training builds
  25. 25.Which of these is a prediction? (a) naming a new fruit photo (b) old emails marked spam (c) recorded spoken words (d) what training builds
  26. 26.True or false: “old emails marked spam” is the model. (a) True (b) False
  27. 27.Which of these is the model? (a) what training builds (b) 500 labelled leaf photos (c) recorded spoken words (d) past weather records
  28. 28.True or false: “what training builds” is a prediction. (a) True (b) False
  29. 29.📦 What happens during training? (a) it learns patterns (b) it prints labels (c) it charges up (d) it takes photos
  30. 30.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) a prediction (b) training data (c) the model
  31. 31.⏩ In machine learning, which comes first: past weather records or the trained program? (a) past weather records (b) the trained program
  32. 32.⏩ In machine learning, which comes first: the learned patterns or naming a new leaf? (a) the learned patterns (b) naming a new leaf
  33. 33.🔁 Training data, the model or a prediction: “naming a new fruit photo”? (a) a prediction (b) training data (c) the model
  34. 34.True or false: “typing a new spoken word” is a prediction. (a) False (b) True
  35. 35.Which of these is training data? (a) typing a new spoken word (b) naming a new fruit photo (c) labelled fruit photos (d) tomorrow’s rain guess
  36. 36.⏩ In machine learning, which comes first: 500 labelled leaf photos or the learned patterns? (a) 500 labelled leaf photos (b) the learned patterns
  37. 37.True or false: “what training builds” is the model. (a) True (b) False
  38. 38.⏩ In machine learning, which comes first: old emails marked spam or the learned patterns? (a) old emails marked spam (b) the learned patterns
  39. 39.Which of these is training data? (a) naming a new fruit photo (b) flagging a new email (c) recorded spoken words (d) the trained program
  40. 40.⏩ In machine learning, which comes first: flagging a new email or the trained program? (a) flagging a new email (b) the trained program

Answer key

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

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