Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 521 · 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) blurry, unclear photos (b) examples of every type (c) labels added at random (d) very few examples
2. 2.True or false: “blurry, unclear photos” is bad for training a model. (a) False (b) True
3. 3.True or false: the message “Last chance! Free gift card inside” should be labelled “not spam”. (a) False (b) True
4. 4.📚 Good or bad for training a model: photos in many lights? (a) bad for training (b) good for training
5. 5.True or false: the message “You won a free phone! Click now!” should be labelled “spam”. (a) True (b) False
6. 6.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “spam”. (a) True (b) False
7. 7.Which of these is good for training a model? (a) blurry, unclear photos (b) labels added at random (c) new data for testing (d) wrong labels
8. 8.True or false: the message “Happy birthday! See you at lunch” should be labelled “not spam”. (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.True or false: “new data for testing” is bad for training a model. (a) True (b) False
11. 11.📚 Good or bad for training a model: examples of every type? (a) good for training (b) bad for training
12. 12.🔍 Which is the odd one out? (a) examples of every type (b) many varied examples (c) blurry, unclear photos (d) new data for testing
13. 13.Which of these is bad for training a model? (a) photos in many lights (b) correct labels (c) clear, sharp examples (d) blurry, unclear photos
14. 14.True or false: the message “Please buy milk on the way home” should be labelled “spam”. (a) False (b) True
15. 15.Which of these is bad for training a model? (a) wrong labels (b) correct labels (c) examples of every type (d) clear, sharp examples
16. 16.True or false: “labels added at random” is good for training a model. (a) False (b) True
17. 17.📚 Good or bad for training a model: very few examples? (a) good for training (b) bad for training
18. 18.🏷️ 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
19. 19.🔍 Which is the odd one out? (a) correct labels (b) labels added at random (c) many varied examples (d) checking labels twice
20. 20.Which of these is good for training a model? (a) copies of one photo (b) wrong labels (c) correct labels (d) blurry, unclear photos
21. 21.📚 Good or bad for training a model: correct labels? (a) bad for training (b) good for training
22. 22.📚 Usually, more good examples make a model… (a) slower to switch on (b) forget everything (c) change colour (d) better at its task
23. 23.🏷️ 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
24. 24.True or false: the message “Last chance! Free gift card inside” should be labelled “spam”. (a) True (b) False
25. 25.🏷️ 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
26. 26.🏷️ 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
27. 27.🏷️ What is a “label” in machine learning? (a) the price (b) a sticker on a laptop (c) the right answer tag (d) the font size
28. 28.Which of these is good for training a model? (a) only one kind of example (b) copies of one photo (c) photos in many lights (d) very few examples
29. 29.True or false: the message “Match practice moved to 5 pm” should be labelled “spam”. (a) True (b) False
30. 30.True or false: the message “Please buy milk on the way home” should be labelled “not spam”. (a) False (b) True
31. 31.🧠 Machine learning is a way for computers to… (a) print pages (b) clean screens (c) learn from data (d) charge faster
32. 32.📚 Good or bad for training a model: wrong labels? (a) bad for training (b) good for training
33. 33.🔍 Which is the odd one out? (a) clear, sharp examples (b) blurry, unclear photos (c) copies of one photo (d) wrong labels
34. 34.🔍 Which is the odd one out? (a) blurry, unclear photos (b) examples of every type (c) very few examples (d) wrong labels
35. 35.🐶 To teach a model to spot dogs in photos, what do you give it? (a) many labelled photos (b) one single photo (c) a song about dogs (d) a list of rules only
36. 36.Which of these is bad for training a model? (a) new data for testing (b) many varied examples (c) very few examples (d) correct labels
37. 37.Which of these is good for training a model? (a) very few examples (b) checking labels twice (c) copies of one photo (d) labels added at random
38. 38.True or false: the message “You won a free phone! Click now!” should be labelled “not spam”. (a) True (b) False
39. 39.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “not spam”. (a) False (b) True
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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