Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 476 · 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.🐶 To teach a model to spot dogs in photos, what do you give it? (a) many labelled photos (b) a song about dogs (c) a list of rules only (d) one single photo
2. 2.🧠 Machine learning is a way for computers to… (a) charge faster (b) print pages (c) learn from data (d) clean screens
3. 3.True or false: “clear, sharp examples” is bad for training a model. (a) False (b) True
4. 4.🔍 Which is the odd one out? (a) testing on training data (b) labels added at random (c) examples of every type (d) wrong labels
5. 5.🔍 Which is the odd one out? (a) clear, sharp examples (b) examples of every type (c) correct labels (d) wrong labels
6. 6.True or false: the message “You won a free phone! Click now!” should be labelled “spam”. (a) False (b) True
7. 7.🔍 Which is the odd one out? (a) labels added at random (b) only one kind of example (c) very few examples (d) many varied examples
8. 8.True or false: the message “Please buy milk on the way home” should be labelled “spam”. (a) False (b) True
9. 9.True or false: the message “Send your password to claim a prize” should be labelled “spam”. (a) True (b) False
10. 10.📚 Good or bad for training a model: wrong labels? (a) good for training (b) bad for training
11. 11.📚 Good or bad for training a model: checking labels twice? (a) good for training (b) bad for training
12. 12.Which of these is bad for training a model? (a) many varied examples (b) correct labels (c) wrong labels (d) photos in many lights
13. 13.🏷️ 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
14. 14.📚 Good or bad for training a model: many varied examples? (a) good for training (b) bad for training
15. 15.📚 Good or bad for training a model: copies of one photo? (a) bad for training (b) good for training
16. 16.📚 Usually, more good examples make a model… (a) change colour (b) slower to switch on (c) better at its task (d) forget everything
17. 17.🔍 Which is the odd one out? (a) very few examples (b) copies of one photo (c) only one kind of example (d) correct labels
18. 18.📚 Good or bad for training a model: very few examples? (a) good for training (b) bad for training
19. 19.🔍 Which is the odd one out? (a) blurry, unclear photos (b) copies of one photo (c) wrong labels (d) checking labels twice
20. 20.🏷️ 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
21. 21.🏷️ 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
22. 22.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “You won a free phone! Click now!” (a) spam (b) not spam
23. 23.🏷️ What is a “label” in machine learning? (a) a sticker on a laptop (b) the price (c) the font size (d) the right answer tag
24. 24.True or false: “wrong labels” is bad for training a model. (a) True (b) False
25. 25.📚 Good or bad for training a model: only one kind of example? (a) good for training (b) bad for training
26. 26.📚 Good or bad for training a model: photos in many lights? (a) bad for training (b) good for training
27. 27.Which of these is good for training a model? (a) wrong labels (b) very few examples (c) clear, sharp examples (d) copies of one photo
28. 28.True or false: the message “Match practice moved to 5 pm” should be labelled “not spam”. (a) True (b) False
29. 29.Which of these is bad for training a model? (a) correct labels (b) clear, sharp examples (c) checking labels twice (d) testing on training data
30. 30.True or false: the message “Share your OTP to get cashback” should be labelled “spam”. (a) False (b) True
31. 31.🏷️ 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
32. 32.Which of these is bad for training a model? (a) photos in many lights (b) very few examples (c) correct labels (d) checking labels twice
33. 33.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Earn ₹50,000 a day from home!!!” (a) spam (b) not spam
34. 34.True or false: “checking labels twice” is good for training a model. (a) True (b) False
35. 35.True or false: “new data for testing” is bad for training a model. (a) False (b) True
36. 36.🔍 Which is the odd one out? (a) checking labels twice (b) very few examples (c) correct labels (d) photos in many lights
37. 37.Which of these is good for training a model? (a) testing on training data (b) new data for testing (c) copies of one photo (d) blurry, unclear photos
38. 38.Which of these is bad for training a model? (a) correct labels (b) many varied examples (c) new data for testing (d) labels added at random
39. 39.Which of these is bad for training a model? (a) examples of every type (b) new data for testing (c) only one kind of example (d) correct labels
40. 40.🔍 Which is the odd one out? (a) clear, sharp examples (b) examples of every type (c) copies of one photo (d) new data for testing

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