Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 94 · 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.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your library book is due on Monday” (a) spam (b) not spam
2. 2.True or false: the message “Send your password to claim a prize” should be labelled “spam”. (a) False (b) True
3. 3.Which of these is good for training a model? (a) very few examples (b) wrong labels (c) checking labels twice (d) only one kind of example
4. 4.🔍 Which is the odd one out? (a) correct labels (b) photos in many lights (c) many varied examples (d) labels added at random
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) spam (b) not spam
6. 6.📚 Usually, more good examples make a model… (a) forget everything (b) slower to switch on (c) better at its task (d) change colour
7. 7.🔍 Which is the odd one out? (a) blurry, unclear photos (b) very few examples (c) testing on training data (d) photos in many lights
8. 8.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Please buy milk on the way home” (a) not spam (b) spam
9. 9.True or false: the message “Your library book is due on Monday” should be labelled “not spam”. (a) False (b) True
10. 10.True or false: “examples of every type” is bad for training a model. (a) True (b) False
11. 11.📚 Good or bad for training a model: new data for testing? (a) good for training (b) bad for training
12. 12.🔍 Which is the odd one out? (a) very few examples (b) correct labels (c) copies of one photo (d) only one kind of example
13. 13.📚 Good or bad for training a model: blurry, unclear photos? (a) bad for training (b) good for training
14. 14.🧠 Machine learning is a way for computers to… (a) learn from data (b) clean screens (c) charge faster (d) print pages
15. 15.🔍 Which is the odd one out? (a) many varied examples (b) correct labels (c) wrong labels (d) new data for testing
16. 16.True or false: the message “Science project groups are on the board” should be labelled “not spam”. (a) True (b) False
17. 17.📚 Good or bad for training a model: correct labels? (a) bad for training (b) good for training
18. 18.🏷️ 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
19. 19.📚 Good or bad for training a model: examples of every type? (a) good for training (b) bad for training
20. 20.Which of these is good for training a model? (a) testing on training data (b) very few examples (c) labels added at random (d) many varied examples
21. 21.🔍 Which is the odd one out? (a) new data for testing (b) checking labels twice (c) blurry, unclear photos (d) examples of every type
22. 22.True or false: the message “Your library book is due on Monday” should be labelled “spam”. (a) False (b) True
23. 23.True or false: “testing on training data” is bad for training a model. (a) False (b) True
24. 24.True or false: “examples of every type” is good for training a model. (a) True (b) False
25. 25.📚 Good or bad for training a model: labels added at random? (a) good for training (b) bad for training
26. 26.True or false: “many varied examples” is good for training a model. (a) True (b) False
27. 27.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will shut down (b) it may get it wrong (c) it will turn yellow (d) it will be perfect
28. 28.🐶 To teach a model to spot dogs in photos, what do you give it? (a) many labelled photos (b) one single photo (c) a list of rules only (d) a song about dogs
29. 29.📚 Good or bad for training a model: many varied examples? (a) bad for training (b) good for training
30. 30.True or false: “blurry, unclear photos” is good for training a model. (a) True (b) False
31. 31.True or false: the message “Happy birthday! See you at lunch” should be labelled “not spam”. (a) True (b) False
32. 32.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “not spam”. (a) False (b) True
33. 33.True or false: the message “Last chance! Free gift card inside” should be labelled “not spam”. (a) False (b) True
34. 34.True or false: the message “Please buy milk on the way home” should be labelled “spam”. (a) False (b) True
35. 35.Which of these is good for training a model? (a) very few examples (b) only one kind of example (c) wrong labels (d) new data for testing
36. 36.📚 Good or bad for training a model: only one kind of example? (a) bad for training (b) good for training
37. 37.🏷️ What is a “label” in machine learning? (a) the font size (b) the right answer tag (c) the price (d) a sticker on a laptop
38. 38.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “not spam”. (a) False (b) True
39. 39.🔍 Which is the odd one out? (a) copies of one photo (b) testing on training data (c) new data for testing (d) blurry, unclear photos
40. 40.🔍 Which is the odd one out? (a) new data for testing (b) very few examples (c) correct labels (d) examples of every type

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