Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 79 · 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 of these is good for training a model? (a) labels added at random (b) only one kind of example (c) correct labels (d) blurry, unclear photos
2. 2.📚 Good or bad for training a model: very few examples? (a) good for training (b) bad for training
3. 3.🏷️ 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
4. 4.Which of these is bad for training a model? (a) testing on training data (b) examples of every type (c) correct labels (d) many varied examples
5. 5.📚 Good or bad for training a model: only one kind of example? (a) good for training (b) bad for training
6. 6.True or false: “wrong labels” is good for training a model. (a) True (b) False
7. 7.Which of these is bad for training a model? (a) only one kind of example (b) photos in many lights (c) new data for testing (d) correct labels
8. 8.🏷️ 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
9. 9.📚 Good or bad for training a model: correct labels? (a) good for training (b) bad for training
10. 10.🏷️ 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
11. 11.🏷️ 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
12. 12.True or false: the message “Your library book is due on Monday” should be labelled “spam”. (a) False (b) True
13. 13.📚 Good or bad for training a model: copies of one photo? (a) bad for training (b) good for training
14. 14.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will shut down (b) it will be perfect (c) it may get it wrong (d) it will turn yellow
15. 15.Which of these is bad for training a model? (a) wrong labels (b) clear, sharp examples (c) correct labels (d) checking labels twice
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 is the odd one out? (a) new data for testing (b) checking labels twice (c) photos in many lights (d) blurry, unclear photos
18. 18.🧠 Machine learning is a way for computers to… (a) clean screens (b) charge faster (c) print pages (d) learn from data
19. 19.🐶 To teach a model to spot dogs in photos, what do you give it? (a) a song about dogs (b) one single photo (c) a list of rules only (d) many labelled photos
20. 20.True or false: “labels added at random” is bad for training a model. (a) False (b) True
21. 21.True or false: the message “Your library book is due on Monday” should be labelled “not spam”. (a) True (b) False
22. 22.Which of these is bad for training a model? (a) photos in many lights (b) copies of one photo (c) many varied examples (d) new data for testing
23. 23.🔍 Which is the odd one out? (a) testing on training data (b) wrong labels (c) very few examples (d) checking labels twice
24. 24.True or false: the message “Happy birthday! See you at lunch” should be labelled “not spam”. (a) True (b) False
25. 25.True or false: the message “Earn ₹50,000 a day from home!!!” 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.🏷️ What is a “label” in machine learning? (a) a sticker on a laptop (b) the right answer tag (c) the font size (d) the price
28. 28.True or false: the message “Happy birthday! See you at lunch” should be labelled “spam”. (a) True (b) False
29. 29.🔍 Which is the odd one out? (a) correct labels (b) labels added at random (c) photos in many lights (d) many varied examples
30. 30.True or false: the message “You won a free phone! Click now!” should be labelled “not spam”. (a) False (b) True
31. 31.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “not spam”. (a) False (b) True
32. 32.True or false: the message “Match practice moved to 5 pm” should be labelled “not spam”. (a) True (b) False
33. 33.True or false: “only one kind of example” is good for training a model. (a) True (b) False
34. 34.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your library book is due on Monday” (a) not spam (b) spam
35. 35.📚 Usually, more good examples make a model… (a) better at its task (b) change colour (c) forget everything (d) slower to switch on
36. 36.📚 Good or bad for training a model: examples of every type? (a) good for training (b) bad for training
37. 37.True or false: “only one kind of example” is bad for training a model. (a) True (b) False
38. 38.True or false: the message “Please buy milk on the way home” should be labelled “spam”. (a) False (b) True
39. 39.🔍 Which is the odd one out? (a) labels added at random (b) correct labels (c) very few examples (d) only one kind of example
40. 40.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “spam”. (a) False (b) True

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