Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 213 · 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: checking labels twice? (a) bad for training (b) good for training
2. 2.True or false: the message “Match practice moved to 5 pm” should be labelled “spam”. (a) True (b) False
3. 3.True or false: “examples of every type” is bad for training a model. (a) False (b) True
4. 4.📚 Good or bad for training a model: only one kind of example? (a) good for training (b) bad for training
5. 5.📚 Good or bad for training a model: testing on training data? (a) bad for training (b) good for training
6. 6.🔍 Which is the odd one out? (a) blurry, unclear photos (b) wrong labels (c) very few examples (d) examples of every type
7. 7.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Please buy milk on the way home” (a) not spam (b) spam
8. 8.Which of these is good for training a model? (a) testing on training data (b) very few examples (c) new data for testing (d) copies of one photo
9. 9.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it may get it wrong (b) it will shut down (c) it will turn yellow (d) it will be perfect
10. 10.True or false: “testing on training data” is bad for training a model. (a) False (b) True
11. 11.🐶 To teach a model to spot dogs in photos, what do you give it? (a) one single photo (b) a list of rules only (c) a song about dogs (d) many labelled photos
12. 12.📚 Usually, more good examples make a model… (a) change colour (b) slower to switch on (c) forget everything (d) better at its task
13. 13.🏷️ 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
14. 14.True or false: “many varied examples” is bad for training a model. (a) True (b) False
15. 15.🏷️ What is a “label” in machine learning? (a) the font size (b) the price (c) a sticker on a laptop (d) the right answer tag
16. 16.Which of these is bad for training a model? (a) many varied examples (b) clear, sharp examples (c) checking labels twice (d) copies of one photo
17. 17.🔍 Which is the odd one out? (a) wrong labels (b) testing on training data (c) many varied examples (d) very few examples
18. 18.True or false: the message “Your library book is due on Monday” should be labelled “spam”. (a) True (b) False
19. 19.True or false: “only one kind of example” is good for training a model. (a) True (b) False
20. 20.Which of these is good for training a model? (a) very few examples (b) wrong labels (c) many varied examples (d) labels added at random
21. 21.True or false: “copies of one photo” is good for training a model. (a) True (b) False
22. 22.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “not spam”. (a) False (b) True
23. 23.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your account is locked, pay ₹99 now” (a) not spam (b) spam
24. 24.Which of these is bad for training a model? (a) testing on training data (b) clear, sharp examples (c) many varied examples (d) examples of every type
25. 25.Which of these is bad for training a model? (a) examples of every type (b) photos in many lights (c) checking labels twice (d) wrong labels
26. 26.True or false: “blurry, unclear photos” is bad for training a model. (a) True (b) False
27. 27.📚 Good or bad for training a model: photos in many lights? (a) good for training (b) bad for training
28. 28.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Send your password to claim a prize” (a) not spam (b) spam
29. 29.Which of these is bad for training a model? (a) photos in many lights (b) many varied examples (c) labels added at random (d) new data for testing
30. 30.Which of these is bad for training a model? (a) examples of every type (b) very few examples (c) new data for testing (d) checking labels twice
31. 31.📚 Good or bad for training a model: many varied examples? (a) good for training (b) bad for training
32. 32.🏷️ 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
33. 33.📚 Good or bad for training a model: blurry, unclear photos? (a) bad for training (b) good for training
34. 34.🏷️ 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
35. 35.True or false: “new data for testing” is good for training a model. (a) False (b) True
36. 36.Which of these is good for training a model? (a) very few examples (b) copies of one photo (c) only one kind of example (d) correct labels
37. 37.🔍 Which is the odd one out? (a) copies of one photo (b) checking labels twice (c) only one kind of example (d) labels added at random
38. 38.🔍 Which is the odd one out? (a) labels added at random (b) photos in many lights (c) testing on training data (d) only one kind of example
39. 39.Which of these is good for training a model? (a) only one kind of example (b) very few examples (c) examples of every type (d) testing on training data
40. 40.📚 Good or bad for training a model: copies of one photo? (a) bad for training (b) good for training

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