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AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 407 · 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: “past weather records” is training data. (a) True (b) False
  2. 2.⏩ In machine learning, which comes first: the trained program or naming a new leaf? (a) the trained program (b) naming a new leaf
  3. 3.Which of these is a prediction? (a) naming a new fruit photo (b) past weather records (c) what training builds (d) the learned patterns
  4. 4.🔁 Training data, the model or a prediction: “naming a new fruit photo”? (a) training data (b) the model (c) a prediction
  5. 5.Which of these is the model? (a) old emails marked spam (b) flagging a new email (c) past weather records (d) the learned patterns
  6. 6.⏩ 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
  7. 7.🧪 Why test a model on NEW examples? (a) to change its name (b) to delete its data (c) to make it slower (d) to see if it works
  8. 8.🔁 Training data, the model or a prediction: “tomorrow’s rain guess”? (a) the model (b) a prediction (c) training data
  9. 9.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) training data (b) a prediction (c) the model
  10. 10.🔁 Training data, the model or a prediction: “the learned patterns”? (a) the model (b) training data (c) a prediction
  11. 11.True or false: “recorded spoken words” is the model. (a) False (b) True
  12. 12.🔁 Training data, the model or a prediction: “past weather records”? (a) a prediction (b) the model (c) training data
  13. 13.🔁 Training data, the model or a prediction: “flagging a new email”? (a) training data (b) the model (c) a prediction
  14. 14.⏩ In machine learning, which comes first: flagging a new email or what training builds? (a) flagging a new email (b) what training builds
  15. 15.📦 What happens during training? (a) it takes photos (b) it charges up (c) it learns patterns (d) it prints labels
  16. 16.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) the model (b) training data (c) a prediction
  17. 17.⏩ In machine learning, which comes first: naming a new leaf or the learned patterns? (a) naming a new leaf (b) the learned patterns
  18. 18.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) a prediction (b) training data (c) the model
  19. 19.⏩ In machine learning, which comes first: what training builds or tomorrow’s rain guess? (a) what training builds (b) tomorrow’s rain guess
  20. 20.True or false: “tomorrow’s rain guess” is a prediction. (a) False (b) True
  21. 21.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) training data (b) a prediction (c) the model
  22. 22.Which of these is the model? (a) recorded spoken words (b) the trained program (c) naming a new fruit photo (d) old emails marked spam
  23. 23.🔁 Training data, the model or a prediction: “the trained program”? (a) the model (b) a prediction (c) training data
  24. 24.Which of these is a prediction? (a) recorded spoken words (b) old emails marked spam (c) the trained program (d) tomorrow’s rain guess
  25. 25.Which of these is training data? (a) what training builds (b) the trained program (c) flagging a new email (d) old emails marked spam
  26. 26.True or false: “the trained program” is training data. (a) True (b) False
  27. 27.True or false: “what training builds” is the model. (a) False (b) True
  28. 28.🔮 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
  29. 29.True or false: “past weather records” is a prediction. (a) True (b) False
  30. 30.Which of these is a prediction? (a) old emails marked spam (b) 500 labelled leaf photos (c) the learned patterns (d) naming a new leaf
  31. 31.⏩ In machine learning, which comes first: tomorrow’s rain guess or old emails marked spam? (a) tomorrow’s rain guess (b) old emails marked spam
  32. 32.True or false: “the learned patterns” is the model. (a) False (b) True
  33. 33.🔁 What is the right order? (a) model, prediction, data (b) prediction, data, model (c) data, model, prediction (d) data, prediction, model
  34. 34.Which of these is the model? (a) past weather records (b) naming a new leaf (c) typing a new spoken word (d) what training builds
  35. 35.True or false: “500 labelled leaf photos” is a prediction. (a) True (b) False
  36. 36.⏩ In machine learning, which comes first: what training builds or recorded spoken words? (a) what training builds (b) recorded spoken words
  37. 37.⏩ In machine learning, which comes first: naming a new leaf or what training builds? (a) naming a new leaf (b) what training builds
  38. 38.⏩ In machine learning, which comes first: recorded spoken words or typing a new spoken word? (a) recorded spoken words (b) typing a new spoken word
  39. 39.⏩ In machine learning, which comes first: typing a new spoken word or old emails marked spam? (a) typing a new spoken word (b) old emails marked spam
  40. 40.⏩ In machine learning, which comes first: tomorrow’s rain guess or recorded spoken words? (a) tomorrow’s rain guess (b) recorded spoken words

Answer key

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

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