Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 570 · 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? “You won a free phone! Click now!” (a) spam (b) not spam
2. 2.Which of these is bad for training a model? (a) very few examples (b) new data for testing (c) clear, sharp examples (d) photos in many lights
3. 3.🧠 Machine learning is a way for computers to… (a) clean screens (b) print pages (c) charge faster (d) learn from data
4. 4.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “spam”. (a) True (b) False
5. 5.🔍 Which is the odd one out? (a) checking labels twice (b) examples of every type (c) photos in many lights (d) labels added at random
6. 6.Which of these is good for training a model? (a) labels added at random (b) photos in many lights (c) blurry, unclear photos (d) only one kind of example
7. 7.📚 Good or bad for training a model: checking labels twice? (a) bad for training (b) good for training
8. 8.🏷️ 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
9. 9.True or false: the message “Please buy milk on the way home” should be labelled “not spam”. (a) False (b) True
10. 10.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Happy birthday! See you at lunch” (a) not spam (b) spam
11. 11.True or false: “new data for testing” is good for training a model. (a) False (b) True
12. 12.🔍 Which is the odd one out? (a) clear, sharp examples (b) new data for testing (c) examples of every type (d) testing on training data
13. 13.🔍 Which is the odd one out? (a) many varied examples (b) copies of one photo (c) testing on training data (d) blurry, unclear photos
14. 14.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “spam”. (a) False (b) True
15. 15.🔍 Which is the odd one out? (a) copies of one photo (b) checking labels twice (c) correct labels (d) clear, sharp examples
16. 16.Which of these is good for training a model? (a) copies of one photo (b) labels added at random (c) wrong labels (d) correct labels
17. 17.Which of these is bad for training a model? (a) examples of every type (b) photos in many lights (c) copies of one photo (d) many varied examples
18. 18.True or false: “checking labels twice” is bad for training a model. (a) False (b) True
19. 19.True or false: “examples of every type” is good for training a model. (a) False (b) True
20. 20.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Last chance! Free gift card inside” (a) not spam (b) spam
21. 21.True or false: the message “Last chance! Free gift card inside” should be labelled “not spam”. (a) False (b) True
22. 22.🔍 Which is the odd one out? (a) correct labels (b) blurry, unclear photos (c) many varied examples (d) photos in many lights
23. 23.True or false: the message “Science project groups are on the board” should be labelled “not spam”. (a) True (b) False
24. 24.Which of these is good for training a model? (a) new data for testing (b) copies of one photo (c) testing on training data (d) labels added at random
25. 25.📚 Good or bad for training a model: only one kind of example? (a) bad for training (b) good for training
26. 26.🔍 Which is the odd one out? (a) blurry, unclear photos (b) wrong labels (c) labels added at random (d) checking labels twice
27. 27.📚 Good or bad for training a model: labels added at random? (a) bad for training (b) good for training
28. 28.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will shut down (b) it will turn yellow (c) it may get it wrong (d) it will be perfect
29. 29.🔍 Which is the odd one out? (a) clear, sharp examples (b) wrong labels (c) correct labels (d) many varied examples
30. 30.Which of these is bad for training a model? (a) wrong labels (b) clear, sharp examples (c) photos in many lights (d) checking labels twice
31. 31.🐶 To teach a model to spot dogs in photos, what do you give it? (a) one single photo (b) a list of rules only (c) a song about dogs (d) many labelled photos
32. 32.True or false: the message “Send your password to claim a prize” should be labelled “spam”. (a) True (b) False
33. 33.📚 Good or bad for training a model: many varied examples? (a) good for training (b) bad for training
34. 34.🏷️ 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
35. 35.📚 Good or bad for training a model: new data for testing? (a) good for training (b) bad for training
36. 36.🏷️ 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
37. 37.True or false: “copies of one photo” is good for training a model. (a) True (b) False
38. 38.True or false: “testing on training data” is good for training a model. (a) False (b) True
39. 39.True or false: “testing on training data” is bad for training a model. (a) True (b) False
40. 40.Which of these is bad for training a model? (a) many varied examples (b) blurry, unclear photos (c) photos in many lights (d) clear, sharp examples

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