Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 235 · 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) very few examples (b) many varied examples (c) blurry, unclear photos (d) copies of one photo
2. 2.True or false: the message “Please buy milk on the way home” should be labelled “not spam”. (a) False (b) True
3. 3.Which of these is good for training a model? (a) correct labels (b) labels added at random (c) very few examples (d) blurry, unclear photos
4. 4.True or false: “new data for testing” is bad for training a model. (a) False (b) True
5. 5.📚 Good or bad for training a model: checking labels twice? (a) bad for training (b) good for training
6. 6.🏷️ 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
7. 7.📚 Good or bad for training a model: photos in many lights? (a) good for training (b) bad for training
8. 8.🐶 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
9. 9.🔍 Which is the odd one out? (a) clear, sharp examples (b) photos in many lights (c) checking labels twice (d) blurry, unclear photos
10. 10.📚 Good or bad for training a model: correct labels? (a) bad for training (b) good for training
11. 11.🔍 Which is the odd one out? (a) photos in many lights (b) many varied examples (c) correct labels (d) testing on training data
12. 12.True or false: “checking labels twice” is good for training a model. (a) True (b) False
13. 13.True or false: the message “You won a free phone! Click now!” should be labelled “not spam”. (a) True (b) False
14. 14.🏷️ 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
15. 15.True or false: the message “Your library book is due on Monday” should be labelled “spam”. (a) True (b) False
16. 16.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will turn yellow (b) it will shut down (c) it will be perfect (d) it may get it wrong
17. 17.🏷️ 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
18. 18.📚 Usually, more good examples make a model… (a) change colour (b) slower to switch on (c) forget everything (d) better at its task
19. 19.🔍 Which is the odd one out? (a) correct labels (b) blurry, unclear photos (c) testing on training data (d) wrong labels
20. 20.Which of these is good for training a model? (a) copies of one photo (b) only one kind of example (c) checking labels twice (d) testing on training data
21. 21.🏷️ What is a “label” in machine learning? (a) a sticker on a laptop (b) the price (c) the right answer tag (d) the font size
22. 22.True or false: “correct labels” is bad for training a model. (a) True (b) False
23. 23.🔍 Which is the odd one out? (a) copies of one photo (b) clear, sharp examples (c) labels added at random (d) very few examples
24. 24.🧠 Machine learning is a way for computers to… (a) charge faster (b) print pages (c) learn from data (d) clean screens
25. 25.True or false: “checking labels twice” is bad for training a model. (a) True (b) False
26. 26.📚 Good or bad for training a model: blurry, unclear photos? (a) good for training (b) bad for training
27. 27.🏷️ 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
28. 28.True or false: the message “Science project groups are on the board” should be labelled “not spam”. (a) False (b) True
29. 29.True or false: “many varied examples” is bad for training a model. (a) True (b) False
30. 30.📚 Good or bad for training a model: copies of one photo? (a) bad for training (b) good for training
31. 31.Which of these is good for training a model? (a) wrong labels (b) clear, sharp examples (c) copies of one photo (d) testing on training data
32. 32.Which of these is good for training a model? (a) very few examples (b) blurry, unclear photos (c) new data for testing (d) copies of one photo
33. 33.🏷️ 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
34. 34.📚 Good or bad for training a model: new data for testing? (a) bad for training (b) good for training
35. 35.🔍 Which is the odd one out? (a) photos in many lights (b) many varied examples (c) clear, sharp examples (d) only one kind of example
36. 36.True or false: “copies of one photo” is good for training a model. (a) False (b) True
37. 37.True or false: “clear, sharp examples” is good for training a model. (a) False (b) True
38. 38.🔍 Which is the odd one out? (a) correct labels (b) checking labels twice (c) clear, sharp examples (d) copies of one photo
39. 39.🏷️ 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
40. 40.True or false: the message “Send your password to claim a prize” should be labelled “spam”. (a) False (b) True

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