Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 560 · 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: only one kind of example? (a) good for training (b) bad for training
2. 2.True or false: “new data for testing” is good for training a model. (a) True (b) False
3. 3.Which of these is bad for training a model? (a) copies of one photo (b) checking labels twice (c) photos in many lights (d) many varied examples
4. 4.True or false: the message “Send your password to claim a prize” should be labelled “not spam”. (a) True (b) False
5. 5.🏷️ 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
6. 6.📚 Good or bad for training a model: checking labels twice? (a) bad for training (b) good for training
7. 7.📚 Good or bad for training a model: correct labels? (a) bad for training (b) good for training
8. 8.True or false: the message “Science project groups are on the board” should be labelled “not spam”. (a) False (b) True
9. 9.📚 Good or bad for training a model: many varied examples? (a) good for training (b) bad for training
10. 10.🧠 Machine learning is a way for computers to… (a) clean screens (b) learn from data (c) print pages (d) charge faster
11. 11.True or false: “photos in many lights” is good for training a model. (a) True (b) False
12. 12.🔍 Which is the odd one out? (a) labels added at random (b) correct labels (c) only one kind of example (d) blurry, unclear photos
13. 13.📚 Good or bad for training a model: wrong labels? (a) bad for training (b) good for training
14. 14.Which of these is good for training a model? (a) testing on training data (b) only one kind of example (c) clear, sharp examples (d) copies of one photo
15. 15.🔍 Which is the odd one out? (a) clear, sharp examples (b) new data for testing (c) photos in many lights (d) only one kind of example
16. 16.📚 Good or bad for training a model: clear, sharp examples? (a) good for training (b) bad for training
17. 17.True or false: “very few examples” is good for training a model. (a) True (b) False
18. 18.True or false: the message “You won a free phone! Click now!” should be labelled “not spam”. (a) False (b) True
19. 19.Which of these is good for training a model? (a) correct labels (b) wrong labels (c) copies of one photo (d) labels added at random
20. 20.True or false: “photos in many lights” is bad for training a model. (a) False (b) True
21. 21.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Match practice moved to 5 pm” (a) not spam (b) spam
22. 22.🔍 Which is the odd one out? (a) wrong labels (b) testing on training data (c) photos in many lights (d) blurry, unclear photos
23. 23.🏷️ 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
24. 24.🏷️ 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
25. 25.🔍 Which is the odd one out? (a) examples of every type (b) labels added at random (c) wrong labels (d) very few examples
26. 26.📚 Good or bad for training a model: photos in many lights? (a) bad for training (b) good for training
27. 27.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “spam”. (a) True (b) False
28. 28.🔍 Which is the odd one out? (a) copies of one photo (b) clear, sharp examples (c) photos in many lights (d) new data for testing
29. 29.True or false: the message “You won a free phone! Click now!” should be labelled “spam”. (a) False (b) True
30. 30.Which of these is good for training a model? (a) very few examples (b) wrong labels (c) copies of one photo (d) many varied examples
31. 31.🔍 Which is the odd one out? (a) copies of one photo (b) only one kind of example (c) checking labels twice (d) testing on training data
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) not spam (b) spam
33. 33.🔍 Which is the odd one out? (a) clear, sharp examples (b) new data for testing (c) many varied examples (d) labels added at random
34. 34.Which of these is good for training a model? (a) labels added at random (b) testing on training data (c) checking labels twice (d) wrong labels
35. 35.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “not spam”. (a) False (b) True
36. 36.True or false: “many varied examples” is good for training a model. (a) True (b) False
37. 37.True or false: “wrong labels” is bad 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) many labelled photos (b) one single photo (c) a song about dogs (d) a list of rules only
39. 39.Which of these is bad for training a model? (a) checking labels twice (b) examples of every type (c) clear, sharp examples (d) labels added at random
40. 40.🏷️ 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

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