Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 241 · 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.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it may get it wrong (b) it will be perfect (c) it will turn yellow (d) it will shut down
2. 2.True or false: the message “Your library book is due on Monday” should be labelled “spam”. (a) True (b) False
3. 3.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Send your password to claim a prize” (a) spam (b) not spam
4. 4.True or false: the message “Send your password to claim a prize” should be labelled “spam”. (a) True (b) False
5. 5.True or false: the message “You won a free phone! Click now!” should be labelled “not spam”. (a) False (b) True
6. 6.True or false: “clear, sharp examples” is good for training a model. (a) False (b) True
7. 7.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “spam”. (a) True (b) False
8. 8.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Last chance! Free gift card inside” (a) spam (b) not spam
9. 9.🔍 Which is the odd one out? (a) only one kind of example (b) wrong labels (c) correct labels (d) blurry, unclear photos
10. 10.📚 Good or bad for training a model: wrong labels? (a) bad for training (b) good for training
11. 11.📚 Good or bad for training a model: blurry, unclear photos? (a) bad for training (b) good for training
12. 12.Which of these is good for training a model? (a) wrong labels (b) only one kind of example (c) photos in many lights (d) very few examples
13. 13.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Share your OTP to get cashback” (a) not spam (b) spam
14. 14.Which of these is bad for training a model? (a) copies of one photo (b) clear, sharp examples (c) examples of every type (d) checking labels twice
15. 15.True or false: the message “Send your password to claim a prize” should be labelled “not spam”. (a) True (b) False
16. 16.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your library book is due on Monday” (a) not spam (b) spam
17. 17.🏷️ What is a “label” in machine learning? (a) a sticker on a laptop (b) the right answer tag (c) the font size (d) the price
18. 18.📚 Good or bad for training a model: only one kind of example? (a) bad for training (b) good for training
19. 19.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Happy birthday! See you at lunch” (a) spam (b) not spam
20. 20.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “You won a free phone! Click now!” (a) not spam (b) spam
21. 21.📚 Good or bad for training a model: checking labels twice? (a) good for training (b) bad for training
22. 22.Which of these is good for training a model? (a) blurry, unclear photos (b) wrong labels (c) testing on training data (d) many varied examples
23. 23.🏷️ 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
24. 24.📚 Good or bad for training a model: correct labels? (a) bad for training (b) good for training
25. 25.Which of these is bad for training a model? (a) many varied examples (b) labels added at random (c) photos in many lights (d) new data for testing
26. 26.Which of these is good for training a model? (a) new data for testing (b) labels added at random (c) only one kind of example (d) blurry, unclear photos
27. 27.📚 Usually, more good examples make a model… (a) change colour (b) better at its task (c) forget everything (d) slower to switch on
28. 28.📚 Good or bad for training a model: photos in many lights? (a) good for training (b) bad for training
29. 29.Which of these is bad for training a model? (a) only one kind of example (b) many varied examples (c) examples of every type (d) correct labels
30. 30.True or false: “many varied examples” is bad for training a model. (a) False (b) True
31. 31.🔍 Which is the odd one out? (a) new data for testing (b) clear, sharp examples (c) testing on training data (d) many varied examples
32. 32.True or false: “very few examples” is bad for training a model. (a) True (b) False
33. 33.🏷️ 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
34. 34.🏷️ 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
35. 35.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “not spam”. (a) True (b) False
36. 36.Which of these is good for training a model? (a) labels added at random (b) examples of every type (c) very few examples (d) wrong labels
37. 37.True or false: “new data for testing” is good for training a model. (a) False (b) True
38. 38.🐶 To teach a model to spot dogs in photos, what do you give it? (a) a song about dogs (b) a list of rules only (c) one single photo (d) many labelled photos
39. 39.🔍 Which is the odd one out? (a) only one kind of example (b) many varied examples (c) testing on training data (d) wrong labels
40. 40.Which of these is bad for training a model? (a) very few examples (b) new data for testing (c) many varied examples (d) clear, sharp examples

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