← Training data, model and prediction lesson New set →

AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 365 · 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: “naming a new fruit photo”? (a) the model (b) training data (c) a prediction
  2. 2.Which of these is a prediction? (a) naming a new leaf (b) labelled fruit photos (c) the learned patterns (d) what training builds
  3. 3.Which of these is a prediction? (a) recorded spoken words (b) the trained program (c) tomorrow’s rain guess (d) 500 labelled leaf photos
  4. 4.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) the model (b) a prediction (c) training data
  5. 5.🔁 Training data, the model or a prediction: “past weather records”? (a) a prediction (b) training data (c) the model
  6. 6.📦 What happens during training? (a) it charges up (b) it takes photos (c) it learns patterns (d) it prints labels
  7. 7.Which of these is training data? (a) naming a new leaf (b) typing a new spoken word (c) naming a new fruit photo (d) old emails marked spam
  8. 8.True or false: “typing a new spoken word” is the model. (a) True (b) False
  9. 9.⏩ In machine learning, which comes first: typing a new spoken word or recorded spoken words? (a) typing a new spoken word (b) recorded spoken words
  10. 10.Which of these is training data? (a) the learned patterns (b) naming a new fruit photo (c) 500 labelled leaf photos (d) typing a new spoken word
  11. 11.🔮 A trained model sees a new photo and says “mango”. This is… (a) training data (b) a password (c) a label error (d) a prediction
  12. 12.Which of these is the model? (a) labelled fruit photos (b) tomorrow’s rain guess (c) the trained program (d) recorded spoken words
  13. 13.⏩ 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
  14. 14.True or false: “naming a new fruit photo” is a prediction. (a) True (b) False
  15. 15.True or false: “what training builds” is a prediction. (a) True (b) False
  16. 16.True or false: “labelled fruit photos” is the model. (a) False (b) True
  17. 17.🔁 What is the right order? (a) data, prediction, model (b) model, prediction, data (c) prediction, data, model (d) data, model, prediction
  18. 18.🧪 Why test a model on NEW examples? (a) to change its name (b) to see if it works (c) to delete its data (d) to make it slower
  19. 19.⏩ In machine learning, which comes first: naming a new fruit photo or what training builds? (a) naming a new fruit photo (b) what training builds
  20. 20.True or false: “500 labelled leaf photos” is training data. (a) False (b) True
  21. 21.True or false: “flagging a new email” is a prediction. (a) True (b) False
  22. 22.🔁 Training data, the model or a prediction: “flagging a new email”? (a) training data (b) a prediction (c) the model
  23. 23.⏩ In machine learning, which comes first: past weather records or the learned patterns? (a) past weather records (b) the learned patterns
  24. 24.True or false: “the learned patterns” is training data. (a) False (b) True
  25. 25.🔁 Training data, the model or a prediction: “naming a new leaf”? (a) the model (b) a prediction (c) training data
  26. 26.True or false: “500 labelled leaf photos” is the model. (a) False (b) True
  27. 27.True or false: “what training builds” is the model. (a) True (b) False
  28. 28.Which of these is training data? (a) the trained program (b) labelled fruit photos (c) what training builds (d) tomorrow’s rain guess
  29. 29.Which of these is training data? (a) recorded spoken words (b) the learned patterns (c) naming a new fruit photo (d) flagging a new email
  30. 30.⏩ In machine learning, which comes first: flagging a new email or 500 labelled leaf photos? (a) flagging a new email (b) 500 labelled leaf photos
  31. 31.True or false: “past weather records” is a prediction. (a) True (b) False
  32. 32.Which of these is a prediction? (a) past weather records (b) 500 labelled leaf photos (c) typing a new spoken word (d) the trained program
  33. 33.Which of these is a prediction? (a) 500 labelled leaf photos (b) old emails marked spam (c) what training builds (d) flagging a new email
  34. 34.True or false: “flagging a new email” is the model. (a) True (b) False
  35. 35.⏩ In machine learning, which comes first: typing a new spoken word or the trained program? (a) typing a new spoken word (b) the trained program
  36. 36.⏩ In machine learning, which comes first: the trained program or old emails marked spam? (a) the trained program (b) old emails marked spam
  37. 37.Which of these is the model? (a) the learned patterns (b) labelled fruit photos (c) typing a new spoken word (d) recorded spoken words
  38. 38.True or false: “past weather records” is training data. (a) True (b) False
  39. 39.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) a prediction (b) the model (c) training data
  40. 40.Which of these is a prediction? (a) old emails marked spam (b) past weather records (c) naming a new fruit photo (d) 500 labelled leaf photos

Answer key

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

Free ai for students lessons, practice and worksheets at talentjr.in/ai-for-students