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AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 194 · 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.🔁 Training data, the model or a prediction: “past weather records”? (a) a prediction (b) training data (c) the model
  2. 2.🔮 A trained model sees a new photo and says “mango”. This is… (a) a label error (b) a password (c) training data (d) a prediction
  3. 3.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) the model (b) a prediction (c) training data
  4. 4.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) the model (b) training data (c) a prediction
  5. 5.True or false: “flagging a new email” is the model. (a) True (b) False
  6. 6.⏩ In machine learning, which comes first: naming a new leaf or what training builds? (a) naming a new leaf (b) what training builds
  7. 7.🔁 Training data, the model or a prediction: “flagging a new email”? (a) training data (b) the model (c) a prediction
  8. 8.🔁 What is the right order? (a) data, model, prediction (b) data, prediction, model (c) prediction, data, model (d) model, prediction, data
  9. 9.Which of these is the model? (a) naming a new fruit photo (b) the trained program (c) naming a new leaf (d) recorded spoken words
  10. 10.⏩ In machine learning, which comes first: 500 labelled leaf photos or naming a new leaf? (a) 500 labelled leaf photos (b) naming a new leaf
  11. 11.True or false: “past weather records” is training data. (a) True (b) False
  12. 12.Which of these is training data? (a) typing a new spoken word (b) naming a new fruit photo (c) past weather records (d) the learned patterns
  13. 13.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) training data (b) a prediction (c) the model
  14. 14.Which of these is a prediction? (a) past weather records (b) 500 labelled leaf photos (c) tomorrow’s rain guess (d) recorded spoken words
  15. 15.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) the model (b) training data (c) a prediction
  16. 16.Which of these is the model? (a) 500 labelled leaf photos (b) the learned patterns (c) naming a new leaf (d) typing a new spoken word
  17. 17.🔁 Training data, the model or a prediction: “what training builds”? (a) training data (b) the model (c) a prediction
  18. 18.🔁 Training data, the model or a prediction: “naming a new fruit photo”? (a) training data (b) the model (c) a prediction
  19. 19.Which of these is training data? (a) the learned patterns (b) what training builds (c) old emails marked spam (d) tomorrow’s rain guess
  20. 20.⏩ In machine learning, which comes first: the learned patterns or tomorrow’s rain guess? (a) the learned patterns (b) tomorrow’s rain guess
  21. 21.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) the model (b) a prediction (c) training data
  22. 22.Which of these is training data? (a) naming a new fruit photo (b) what training builds (c) flagging a new email (d) recorded spoken words
  23. 23.⏩ In machine learning, which comes first: what training builds or old emails marked spam? (a) what training builds (b) old emails marked spam
  24. 24.⏩ In machine learning, which comes first: past weather records or what training builds? (a) past weather records (b) what training builds
  25. 25.⏩ 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
  26. 26.True or false: “typing a new spoken word” is a prediction. (a) True (b) False
  27. 27.Which of these is training data? (a) the trained program (b) what training builds (c) naming a new fruit photo (d) labelled fruit photos
  28. 28.True or false: “labelled fruit photos” is training data. (a) False (b) True
  29. 29.⏩ 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
  30. 30.⏩ In machine learning, which comes first: 500 labelled leaf photos or what training builds? (a) 500 labelled leaf photos (b) what training builds
  31. 31.True or false: “typing a new spoken word” is the model. (a) True (b) False
  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.📦 What happens during training? (a) it prints labels (b) it charges up (c) it learns patterns (d) it takes photos
  34. 34.⏩ In machine learning, which comes first: naming a new fruit photo or the learned patterns? (a) naming a new fruit photo (b) the learned patterns
  35. 35.True or false: “the learned patterns” is the model. (a) False (b) True
  36. 36.⏩ In machine learning, which comes first: the learned patterns or recorded spoken words? (a) the learned patterns (b) recorded spoken words
  37. 37.True or false: “500 labelled leaf photos” is the model. (a) False (b) True
  38. 38.True or false: “old emails marked spam” is the model. (a) True (b) False
  39. 39.🧪 Why test a model on NEW examples? (a) to change its name (b) to delete its data (c) to see if it works (d) to make it slower
  40. 40.🔁 Training data, the model or a prediction: “the trained program”? (a) a prediction (b) training data (c) the model

Answer key

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

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