Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 583 · 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) only one kind of example (b) many varied examples (c) wrong labels (d) labels added at random
2. 2.🔍 Which is the odd one out? (a) correct labels (b) clear, sharp examples (c) examples of every type (d) blurry, unclear photos
3. 3.🐶 To teach a model to spot dogs in photos, what do you give it? (a) one single photo (b) many labelled photos (c) a song about dogs (d) a list of rules only
4. 4.🔍 Which is the odd one out? (a) very few examples (b) checking labels twice (c) many varied examples (d) photos in many lights
5. 5.Which of these is good for training a model? (a) copies of one photo (b) many varied examples (c) labels added at random (d) wrong labels
6. 6.Which of these is bad for training a model? (a) correct labels (b) only one kind of example (c) many varied examples (d) examples of every type
7. 7.Which of these is bad for training a model? (a) many varied examples (b) new data for testing (c) very few examples (d) examples of every type
8. 8.True or false: “copies of one photo” is good for training a model. (a) True (b) False
9. 9.🏷️ 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
10. 10.🔍 Which is the odd one out? (a) testing on training data (b) correct labels (c) very few examples (d) labels added at random
11. 11.True or false: the message “You won a free phone! Click now!” should be labelled “not spam”. (a) False (b) True
12. 12.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will turn yellow (b) it may get it wrong (c) it will shut down (d) it will be perfect
13. 13.🔍 Which is the odd one out? (a) examples of every type (b) photos in many lights (c) testing on training data (d) correct labels
14. 14.🧠 Machine learning is a way for computers to… (a) learn from data (b) print pages (c) charge faster (d) clean screens
15. 15.📚 Good or bad for training a model: labels added at random? (a) good for training (b) bad for training
16. 16.True or false: the message “Science project groups are on the board” should be labelled “spam”. (a) True (b) False
17. 17.True or false: “labels added at random” is bad for training a model. (a) True (b) False
18. 18.📚 Usually, more good examples make a model… (a) forget everything (b) better at its task (c) change colour (d) slower to switch on
19. 19.True or false: “correct labels” is good for training a model. (a) False (b) True
20. 20.True or false: “photos in many lights” is good for training a model. (a) True (b) False
21. 21.🔍 Which is the odd one out? (a) wrong labels (b) photos in many lights (c) correct labels (d) clear, sharp examples
22. 22.🔍 Which is the odd one out? (a) new data for testing (b) examples of every type (c) clear, sharp examples (d) only one kind of example
23. 23.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “spam”. (a) False (b) True
24. 24.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Share your OTP to get cashback” (a) spam (b) not spam
25. 25.True or false: “only one kind of example” is bad for training a model. (a) True (b) False
26. 26.📚 Good or bad for training a model: clear, sharp examples? (a) good for training (b) bad for training
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.🏷️ 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
29. 29.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “spam”. (a) False (b) True
30. 30.Which of these is good for training a model? (a) blurry, unclear photos (b) examples of every type (c) very few examples (d) wrong labels
31. 31.📚 Good or bad for training a model: copies of one photo? (a) bad for training (b) good for training
32. 32.True or false: “examples of every type” is bad for training a model. (a) False (b) True
33. 33.True or false: the message “You won a free phone! Click now!” should be labelled “spam”. (a) True (b) False
34. 34.Which of these is good for training a model? (a) clear, sharp examples (b) very few examples (c) copies of one photo (d) wrong labels
35. 35.📚 Good or bad for training a model: checking labels twice? (a) good for training (b) bad for training
36. 36.Which of these is good for training a model? (a) only one kind of example (b) wrong labels (c) checking labels twice (d) very few examples
37. 37.Which of these is bad for training a model? (a) correct labels (b) many varied examples (c) wrong labels (d) photos in many lights
38. 38.📚 Good or bad for training a model: only one kind of example? (a) good for training (b) bad for training
39. 39.🏷️ 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
40. 40.📚 Good or bad for training a model: testing on training data? (a) bad for training (b) good for training

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