Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 515 · 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) wrong labels (b) labels added at random (c) examples of every type (d) very few examples
2. 2.🐶 To teach a model to spot dogs in photos, what do you give it? (a) many labelled photos (b) a list of rules only (c) one single photo (d) a song about dogs
3. 3.🏷️ 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
4. 4.📚 Good or bad for training a model: new data for testing? (a) bad for training (b) good for training
5. 5.📚 Good or bad for training a model: labels added at random? (a) good for training (b) bad for training
6. 6.📚 Good or bad for training a model: correct labels? (a) good for training (b) bad for training
7. 7.🧠 Machine learning is a way for computers to… (a) clean screens (b) print pages (c) charge faster (d) learn from data
8. 8.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Happy birthday! See you at lunch” (a) spam (b) not spam
9. 9.Which of these is good for training a model? (a) labels added at random (b) correct labels (c) testing on training data (d) very few examples
10. 10.🔍 Which is the odd one out? (a) labels added at random (b) checking labels twice (c) copies of one photo (d) blurry, unclear photos
11. 11.🏷️ 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
12. 12.🔍 Which is the odd one out? (a) wrong labels (b) many varied examples (c) photos in many lights (d) new data for testing
13. 13.📚 Good or bad for training a model: testing on training data? (a) bad for training (b) good for training
14. 14.True or false: the message “You won a free phone! Click now!” should be labelled “not spam”. (a) True (b) False
15. 15.📚 Good or bad for training a model: clear, sharp examples? (a) good for training (b) bad for training
16. 16.True or false: “examples of every type” is good for training a model. (a) False (b) True
17. 17.📚 Usually, more good examples make a model… (a) slower to switch on (b) forget everything (c) better at its task (d) change colour
18. 18.Which of these is good for training a model? (a) copies of one photo (b) very few examples (c) blurry, unclear photos (d) many varied examples
19. 19.Which of these is bad for training a model? (a) many varied examples (b) testing on training data (c) examples of every type (d) new data for testing
20. 20.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Share your OTP to get cashback” (a) not spam (b) spam
21. 21.True or false: the message “Please buy milk on the way home” should be labelled “not spam”. (a) True (b) False
22. 22.🏷️ 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
23. 23.Which of these is good for training a model? (a) new data for testing (b) only one kind of example (c) wrong labels (d) very few examples
24. 24.🔍 Which is the odd one out? (a) correct labels (b) new data for testing (c) clear, sharp examples (d) testing on training data
25. 25.True or false: “checking labels twice” is bad for training a model. (a) True (b) False
26. 26.🔍 Which is the odd one out? (a) clear, sharp examples (b) copies of one photo (c) correct labels (d) examples of every type
27. 27.🏷️ 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
28. 28.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Send your password to claim a prize” (a) spam (b) not spam
29. 29.True or false: the message “Match practice moved to 5 pm” should be labelled “not spam”. (a) True (b) False
30. 30.Which of these is bad for training a model? (a) very few examples (b) examples of every type (c) many varied examples (d) new data for testing
31. 31.True or false: the message “Your library book is due on Monday” should be labelled “spam”. (a) False (b) True
32. 32.🔍 Which is the odd one out? (a) checking labels twice (b) examples of every type (c) new data for testing (d) labels added at random
33. 33.📚 Good or bad for training a model: only one kind of example? (a) bad for training (b) good for training
34. 34.True or false: “testing on training data” is bad for training a model. (a) False (b) True
35. 35.🔍 Which is the odd one out? (a) correct labels (b) new data for testing (c) many varied examples (d) very few examples
36. 36.True or false: the message “Send your password to claim a prize” should be labelled “not spam”. (a) True (b) False
37. 37.True or false: the message “Please buy milk on the way home” should be labelled “spam”. (a) False (b) True
38. 38.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “not spam”. (a) True (b) False
39. 39.🔍 Which is the odd one out? (a) copies of one photo (b) only one kind of example (c) testing on training data (d) photos in many lights
40. 40.Which of these is bad for training a model? (a) examples of every type (b) photos in many lights (c) new data for testing (d) only one kind of example

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