Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 491 · 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.🏷️ What is a “label” in machine learning? (a) the price (b) a sticker on a laptop (c) the font size (d) the right answer tag
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: blurry, unclear photos? (a) bad for training (b) good for training
4. 4.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Please buy milk on the way home” (a) spam (b) not spam
5. 5.True or false: “many varied examples” is good for training a model. (a) False (b) True
6. 6.🏷️ 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
7. 7.Which of these is bad for training a model? (a) photos in many lights (b) many varied examples (c) examples of every type (d) testing on training data
8. 8.📚 Good or bad for training a model: only one kind of example? (a) good for training (b) bad for training
9. 9.🧠 Machine learning is a way for computers to… (a) print pages (b) clean screens (c) charge faster (d) learn from data
10. 10.🔍 Which is the odd one out? (a) new data for testing (b) examples of every type (c) blurry, unclear photos (d) clear, sharp examples
11. 11.📚 Good or bad for training a model: correct labels? (a) good for training (b) bad for training
12. 12.🏷️ 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
13. 13.True or false: “labels added at random” is bad for training a model. (a) True (b) False
14. 14.True or false: the message “Please buy milk on the way home” should be labelled “spam”. (a) True (b) False
15. 15.Which of these is bad for training a model? (a) copies of one photo (b) clear, sharp examples (c) checking labels twice (d) many varied examples
16. 16.📚 Good or bad for training a model: clear, sharp examples? (a) bad for training (b) good for training
17. 17.True or false: “checking labels twice” is good for training a model. (a) True (b) False
18. 18.📚 Usually, more good examples make a model… (a) change colour (b) slower to switch on (c) forget everything (d) better at its task
19. 19.Which of these is good for training a model? (a) only one kind of example (b) blurry, unclear photos (c) wrong labels (d) correct labels
20. 20.True or false: “blurry, unclear photos” is good 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? “Send your password to claim a prize” (a) spam (b) not spam
22. 22.🔍 Which is the odd one out? (a) many varied examples (b) correct labels (c) photos in many lights (d) wrong labels
23. 23.🐶 To teach a model to spot dogs in photos, what do you give it? (a) a list of rules only (b) one single photo (c) many labelled photos (d) a song about dogs
24. 24.📚 Good or bad for training a model: many varied examples? (a) bad for training (b) good for training
25. 25.True or false: the message “Science project groups are on the board” should be labelled “not spam”. (a) False (b) True
26. 26.True or false: “checking labels twice” is bad for training a model. (a) True (b) False
27. 27.🔍 Which is the odd one out? (a) many varied examples (b) very few examples (c) wrong labels (d) copies of one photo
28. 28.🔍 Which is the odd one out? (a) testing on training data (b) blurry, unclear photos (c) labels added at random (d) examples of every type
29. 29.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Science project groups are on the board” (a) not spam (b) spam
30. 30.🏷️ 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
31. 31.🥭 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 be perfect (d) it will turn yellow
32. 32.Which of these is bad for training a model? (a) correct labels (b) wrong labels (c) examples of every type (d) many varied examples
33. 33.🏷️ 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
34. 34.Which of these is good for training a model? (a) checking labels twice (b) wrong labels (c) very few examples (d) copies of one photo
35. 35.📚 Good or bad for training a model: new data for testing? (a) bad for training (b) good for training
36. 36.Which of these is good for training a model? (a) very few examples (b) blurry, unclear photos (c) wrong labels (d) many varied examples
37. 37.True or false: the message “You won a free phone! Click now!” should be labelled “not spam”. (a) False (b) True
38. 38.Which of these is bad for training a model? (a) examples of every type (b) blurry, unclear photos (c) clear, sharp examples (d) correct labels
39. 39.📚 Good or bad for training a model: wrong labels? (a) good for training (b) bad for training
40. 40.True or false: “new data for testing” is bad for training a model. (a) True (b) False

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