Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 50 · 40 questions

AI tip (Show, label, learn): Machine learning learns patterns from many labelled examples — a label is the right answer tag on each example. Good for training: many varied examples, correct labels, every type the model will meet, and separate new data for testing. Bad for training: very few examples, wrong or random labels, only one kind of example, blurry examples, testing on the training data.

1. 1.📚 Good or bad for training a model: photos in many lights? (a) good for training (b) bad for training
2. 2.📚 Good or bad for training a model: very few examples? (a) good for training (b) bad for training
3. 3.📚 Good or bad for training a model: many varied examples? (a) bad for training (b) good for training
4. 4.Which of these is good for training a model? (a) testing on training data (b) wrong labels (c) labels added at random (d) checking labels twice
5. 5.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “not spam”. (a) False (b) True
6. 6.📚 Good or bad for training a model: examples of every type? (a) bad for training (b) good for training
7. 7.📚 Good or bad for training a model: correct labels? (a) good for training (b) bad for training
8. 8.🔍 Which is the odd one out? (a) examples of every type (b) many varied examples (c) very few examples (d) new data for testing
9. 9.True or false: “very few examples” is bad for training a model. (a) False (b) True
10. 10.Which of these is bad for training a model? (a) only one kind of example (b) checking labels twice (c) many varied examples (d) photos in many lights
11. 11.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Match practice moved to 5 pm” (a) spam (b) not spam
12. 12.📚 Good or bad for training a model: labels added at random? (a) bad for training (b) good for training
13. 13.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “not spam”. (a) True (b) False
14. 14.🔍 Which is the odd one out? (a) checking labels twice (b) examples of every type (c) new data for testing (d) wrong labels
15. 15.True or false: “correct labels” is good for training a model. (a) True (b) False
16. 16.📚 Good or bad for training a model: clear, sharp examples? (a) good for training (b) bad for training
17. 17.Which of these is bad for training a model? (a) new data for testing (b) many varied examples (c) photos in many lights (d) copies of one photo
18. 18.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Earn ₹50,000 a day from home!!!” (a) not spam (b) spam
19. 19.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your account is locked, pay ₹99 now” (a) spam (b) not spam
20. 20.🔍 Which is the odd one out? (a) blurry, unclear photos (b) many varied examples (c) only one kind of example (d) very few examples
21. 21.Which of these is bad for training a model? (a) very few examples (b) correct labels (c) photos in many lights (d) examples of every type
22. 22.📚 Good or bad for training a model: new data for testing? (a) good for training (b) bad for training
23. 23.📚 Good or bad for training a model: testing on training data? (a) good for training (b) bad for training
24. 24.🔍 Which is the odd one out? (a) examples of every type (b) blurry, unclear photos (c) checking labels twice (d) clear, sharp examples
25. 25.🔍 Which is the odd one out? (a) photos in many lights (b) examples of every type (c) many varied examples (d) only one kind of example
26. 26.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will be perfect (b) it will turn yellow (c) it may get it wrong (d) it will shut down
27. 27.Which of these is good for training a model? (a) only one kind of example (b) testing on training data (c) examples of every type (d) wrong labels
28. 28.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “The class picnic is on Friday at 8 am” (a) spam (b) not spam
29. 29.📚 Usually, more good examples make a model… (a) change colour (b) forget everything (c) better at its task (d) slower to switch on
30. 30.True or false: the message “Your library book is due on Monday” should be labelled “not spam”. (a) True (b) False
31. 31.True or false: “very few examples” is good for training a model. (a) True (b) False
32. 32.📚 Good or bad for training a model: copies of one photo? (a) good for training (b) bad for training
33. 33.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your library book is due on Monday” (a) spam (b) not spam
34. 34.True or false: “wrong labels” is bad for training a model. (a) True (b) False
35. 35.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Science project groups are on the board” (a) spam (b) not spam
36. 36.Which of these is good for training a model? (a) only one kind of example (b) very few examples (c) copies of one photo (d) new data for testing
37. 37.🔍 Which is the odd one out? (a) blurry, unclear photos (b) testing on training data (c) labels added at random (d) clear, sharp examples
38. 38.True or false: the message “Happy birthday! See you at lunch” should be labelled “not spam”. (a) False (b) True
39. 39.Which of these is good for training a model? (a) labels added at random (b) blurry, unclear photos (c) correct labels (d) only one kind of example
40. 40.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Happy birthday! See you at lunch” (a) not spam (b) spam

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