Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 391 · 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.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “not spam”. (a) True (b) False
2. 2.🧠 Machine learning is a way for computers to… (a) clean screens (b) learn from data (c) print pages (d) charge faster
3. 3.🔍 Which is the odd one out? (a) correct labels (b) wrong labels (c) many varied examples (d) photos in many lights
4. 4.Which of these is good for training a model? (a) new data for testing (b) very few examples (c) testing on training data (d) copies of one photo
5. 5.🏷️ 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
6. 6.True or false: “new data for testing” is good for training a model. (a) True (b) False
7. 7.True or false: “blurry, unclear photos” is bad for training a model. (a) True (b) False
8. 8.Which of these is bad for training a model? (a) new data for testing (b) clear, sharp examples (c) only one kind of example (d) correct labels
9. 9.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “spam”. (a) True (b) False
10. 10.🏷️ 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
11. 11.True or false: “clear, sharp examples” is good for training a model. (a) True (b) False
12. 12.True or false: “testing on training data” is bad for training a model. (a) True (b) False
13. 13.Which of these is good for training a model? (a) copies of one photo (b) clear, sharp examples (c) only one kind of example (d) testing on training data
14. 14.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your account is locked, pay ₹99 now” (a) spam (b) not spam
15. 15.Which of these is good for training a model? (a) very few examples (b) copies of one photo (c) testing on training data (d) examples of every type
16. 16.True or false: “checking labels twice” is good for training a model. (a) False (b) True
17. 17.🔍 Which is the odd one out? (a) examples of every type (b) only one kind of example (c) copies of one photo (d) blurry, unclear photos
18. 18.🔍 Which is the odd one out? (a) photos in many lights (b) blurry, unclear photos (c) very few examples (d) testing on training data
19. 19.📚 Good or bad for training a model: only one kind of example? (a) good for training (b) bad for training
20. 20.True or false: the message “You won a free phone! Click now!” should be labelled “not spam”. (a) False (b) True
21. 21.Which of these is good for training a model? (a) photos in many lights (b) labels added at random (c) wrong labels (d) blurry, unclear photos
22. 22.📚 Good or bad for training a model: labels added at random? (a) good for training (b) bad for training
23. 23.True or false: the message “Send your password to claim a prize” should be labelled “not spam”. (a) True (b) False
24. 24.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Please buy milk on the way home” (a) not spam (b) spam
25. 25.True or false: “examples of every type” is bad for training a model. (a) True (b) False
26. 26.Which of these is good for training a model? (a) very few examples (b) only one kind of example (c) copies of one photo (d) many varied examples
27. 27.True or false: “testing on training data” is good for training a model. (a) True (b) False
28. 28.Which of these is bad for training a model? (a) clear, sharp examples (b) blurry, unclear photos (c) many varied examples (d) examples of every type
29. 29.📚 Good or bad for training a model: photos in many lights? (a) bad for training (b) good for training
30. 30.🔍 Which is the odd one out? (a) many varied examples (b) checking labels twice (c) correct labels (d) copies of one photo
31. 31.🔍 Which is the odd one out? (a) clear, sharp examples (b) correct labels (c) photos in many lights (d) labels added at random
32. 32.🏷️ What is a “label” in machine learning? (a) the price (b) the right answer tag (c) a sticker on a laptop (d) the font size
33. 33.True or false: “examples of every type” is good for training a model. (a) False (b) True
34. 34.🐶 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) many labelled photos (d) a song about dogs
35. 35.📚 Usually, more good examples make a model… (a) change colour (b) better at its task (c) forget everything (d) slower to switch on
36. 36.🔍 Which is the odd one out? (a) many varied examples (b) checking labels twice (c) photos in many lights (d) only one kind of example
37. 37.🔍 Which is the odd one out? (a) very few examples (b) labels added at random (c) clear, sharp examples (d) blurry, unclear photos
38. 38.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “not spam”. (a) True (b) False
39. 39.🏷️ 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
40. 40.📚 Good or bad for training a model: clear, sharp examples? (a) good for training (b) bad for training

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