Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 280 · 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.🏷️ What is a “label” in machine learning? (a) the font size (b) the price (c) a sticker on a laptop (d) the right answer tag
2. 2.True or false: the message “Last chance! Free gift card inside” should be labelled “spam”. (a) False (b) True
3. 3.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Earn ₹50,000 a day from home!!!” (a) spam (b) not spam
4. 4.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “not spam”. (a) True (b) False
5. 5.Which of these is good for training a model? (a) blurry, unclear photos (b) testing on training data (c) new data for testing (d) copies of one photo
6. 6.True or false: “only one kind of example” is bad for training a model. (a) False (b) True
7. 7.🔍 Which is the odd one out? (a) correct labels (b) testing on training data (c) checking labels twice (d) new data for testing
8. 8.📚 Good or bad for training a model: clear, sharp examples? (a) good for training (b) bad for training
9. 9.Which of these is bad for training a model? (a) photos in many lights (b) correct labels (c) clear, sharp examples (d) testing on training data
10. 10.True or false: “blurry, unclear photos” is good for training a model. (a) True (b) False
11. 11.📚 Good or bad for training a model: wrong labels? (a) bad for training (b) good for training
12. 12.🏷️ 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
13. 13.📚 Good or bad for training a model: many varied examples? (a) bad for training (b) good for training
14. 14.🔍 Which is the odd one out? (a) very few examples (b) copies of one photo (c) wrong labels (d) new data for testing
15. 15.True or false: “copies of one photo” is good for training a model. (a) False (b) True
16. 16.True or false: the message “Please buy milk on the way home” should be labelled “not spam”. (a) False (b) True
17. 17.True or false: “very few examples” is good for training a model. (a) False (b) True
18. 18.🔍 Which is the odd one out? (a) correct labels (b) blurry, unclear photos (c) wrong labels (d) only one kind of example
19. 19.🐶 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
20. 20.📚 Usually, more good examples make a model… (a) change colour (b) slower to switch on (c) forget everything (d) better at its task
21. 21.📚 Good or bad for training a model: new data for testing? (a) bad for training (b) good for training
22. 22.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “spam”. (a) True (b) False
23. 23.🔍 Which is the odd one out? (a) copies of one photo (b) correct labels (c) examples of every type (d) checking labels twice
24. 24.True or false: “examples of every type” is bad for training a model. (a) False (b) True
25. 25.🏷️ 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
26. 26.🧠 Machine learning is a way for computers to… (a) learn from data (b) print pages (c) charge faster (d) clean screens
27. 27.🔍 Which is the odd one out? (a) only one kind of example (b) checking labels twice (c) very few examples (d) labels added at random
28. 28.🏷️ 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
29. 29.Which of these is good for training a model? (a) only one kind of example (b) very few examples (c) examples of every type (d) copies of one photo
30. 30.True or false: “testing on training data” is good for training a model. (a) False (b) True
31. 31.Which of these is good for training a model? (a) only one kind of example (b) blurry, unclear photos (c) very few examples (d) correct labels
32. 32.🏷️ 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
33. 33.📚 Good or bad for training a model: examples of every type? (a) bad for training (b) good for training
34. 34.📚 Good or bad for training a model: blurry, unclear photos? (a) bad for training (b) good for training
35. 35.True or false: the message “You won a free phone! Click now!” should be labelled “spam”. (a) False (b) True
36. 36.🔍 Which is the odd one out? (a) very few examples (b) labels added at random (c) only one kind of example (d) clear, sharp examples
37. 37.📚 Good or bad for training a model: correct labels? (a) good for training (b) bad for training
38. 38.🔍 Which is the odd one out? (a) only one kind of example (b) photos in many lights (c) labels added at random (d) blurry, unclear photos
39. 39.Which of these is bad for training a model? (a) photos in many lights (b) examples of every type (c) wrong labels (d) many varied examples
40. 40.🔍 Which is the odd one out? (a) blurry, unclear photos (b) examples of every type (c) very few examples (d) labels added at random

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