Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 575 · 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.🔍 Which is the odd one out? (a) checking labels twice (b) new data for testing (c) very few examples (d) many varied examples
2. 2.📚 Good or bad for training a model: very few examples? (a) bad for training (b) good for training
3. 3.True or false: the message “Send your password to claim a prize” should be labelled “spam”. (a) True (b) False
4. 4.📚 Good or bad for training a model: correct labels? (a) bad for training (b) good for training
5. 5.True or false: “photos in many lights” is good for training a model. (a) True (b) False
6. 6.📚 Good or bad for training a model: checking labels twice? (a) bad for training (b) good for training
7. 7.True or false: “examples of every type” is good for training a model. (a) False (b) True
8. 8.Which of these is good for training a model? (a) only one kind of example (b) very few examples (c) blurry, unclear photos (d) many varied examples
9. 9.Which of these is good for training a model? (a) labels added at random (b) clear, sharp examples (c) very few examples (d) testing on training data
10. 10.True or false: “testing on training data” is bad for training a model. (a) False (b) True
11. 11.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will be perfect (b) it will shut down (c) it will turn yellow (d) it may get it wrong
12. 12.Which of these is bad for training a model? (a) checking labels twice (b) wrong labels (c) many varied examples (d) correct labels
13. 13.📚 Usually, more good examples make a model… (a) forget everything (b) slower to switch on (c) change colour (d) better at its task
14. 14.🏷️ 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
15. 15.📚 Good or bad for training a model: wrong labels? (a) good for training (b) bad for training
16. 16.🏷️ 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
17. 17.Which of these is bad for training a model? (a) photos in many lights (b) blurry, unclear photos (c) correct labels (d) new data for testing
18. 18.🔍 Which is the odd one out? (a) only one kind of example (b) labels added at random (c) wrong labels (d) new data for testing
19. 19.True or false: the message “Last chance! Free gift card inside” should be labelled “spam”. (a) False (b) True
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.🔍 Which is the odd one out? (a) checking labels twice (b) clear, sharp examples (c) wrong labels (d) correct labels
22. 22.🐶 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
23. 23.True or false: “many varied examples” is good for training a model. (a) False (b) True
24. 24.📚 Good or bad for training a model: testing on training data? (a) bad for training (b) good for training
25. 25.🔍 Which is the odd one out? (a) examples of every type (b) many varied examples (c) clear, sharp examples (d) testing on training data
26. 26.🧠 Machine learning is a way for computers to… (a) learn from data (b) clean screens (c) print pages (d) charge faster
27. 27.🔍 Which is the odd one out? (a) testing on training data (b) photos in many lights (c) only one kind of example (d) very few examples
28. 28.🏷️ What is a “label” in machine learning? (a) the right answer tag (b) the price (c) a sticker on a laptop (d) the font size
29. 29.Which of these is bad for training a model? (a) photos in many lights (b) checking labels twice (c) new data for testing (d) only one kind of example
30. 30.Which of these is good for training a model? (a) labels added at random (b) checking labels twice (c) blurry, unclear photos (d) copies of one photo
31. 31.Which of these is bad for training a model? (a) labels added at random (b) many varied examples (c) correct labels (d) examples of every type
32. 32.🔍 Which is the odd one out? (a) checking labels twice (b) new data for testing (c) labels added at random (d) clear, sharp examples
33. 33.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “not spam”. (a) True (b) False
34. 34.True or false: “wrong labels” is good for training a model. (a) True (b) False
35. 35.📚 Good or bad for training a model: copies of one photo? (a) bad for training (b) good for training
36. 36.True or false: the message “Science project groups are on the board” should be labelled “spam”. (a) False (b) True
37. 37.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “not spam”. (a) True (b) False
38. 38.📚 Good or bad for training a model: examples of every type? (a) good for training (b) bad for training
39. 39.True or false: the message “Happy birthday! See you at lunch” should be labelled “spam”. (a) True (b) False
40. 40.📚 Good or bad for training a model: new data for testing? (a) bad for training (b) good for training

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