Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 109 · 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.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Science project groups are on the board” (a) not spam (b) spam
2. 2.Which of these is good for training a model? (a) testing on training data (b) wrong labels (c) very few examples (d) clear, sharp examples
3. 3.🔍 Which is the odd one out? (a) wrong labels (b) testing on training data (c) very few examples (d) examples of every type
4. 4.True or false: the message “Last chance! Free gift card inside” should be labelled “spam”. (a) False (b) True
5. 5.True or false: “testing on training data” is good for training a model. (a) False (b) True
6. 6.True or false: “correct labels” is good for training a model. (a) False (b) True
7. 7.🏷️ 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
8. 8.True or false: “blurry, unclear photos” is bad for training a model. (a) False (b) True
9. 9.Which of these is bad for training a model? (a) new data for testing (b) examples of every type (c) checking labels twice (d) blurry, unclear photos
10. 10.📚 Usually, more good examples make a model… (a) forget everything (b) better at its task (c) slower to switch on (d) change colour
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) spam (b) not spam
12. 12.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “not spam”. (a) True (b) False
13. 13.True or false: “copies of one photo” is good for training a model. (a) False (b) True
14. 14.📚 Good or bad for training a model: labels added at random? (a) bad for training (b) good for training
15. 15.🔍 Which is the odd one out? (a) new data for testing (b) many varied examples (c) correct labels (d) labels added at random
16. 16.📚 Good or bad for training a model: wrong labels? (a) bad for training (b) good for training
17. 17.Which of these is good for training a model? (a) checking labels twice (b) copies of one photo (c) very few examples (d) testing on training data
18. 18.Which of these is good for training a model? (a) photos in many lights (b) copies of one photo (c) only one kind of example (d) wrong labels
19. 19.Which of these is bad for training a model? (a) testing on training data (b) correct labels (c) examples of every type (d) many varied examples
20. 20.True or false: “correct labels” is bad for training a model. (a) True (b) False
21. 21.🧠 Machine learning is a way for computers to… (a) charge faster (b) clean screens (c) print pages (d) learn from data
22. 22.True or false: “new data for testing” is bad for training a model. (a) False (b) True
23. 23.True or false: the message “Happy birthday! See you at lunch” should be labelled “spam”. (a) False (b) True
24. 24.📚 Good or bad for training a model: examples of every type? (a) bad for training (b) good for training
25. 25.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “spam”. (a) True (b) False
26. 26.True or false: the message “Your library book is due on Monday” should be labelled “not spam”. (a) False (b) True
27. 27.📚 Good or bad for training a model: blurry, unclear photos? (a) good for training (b) bad for training
28. 28.📚 Good or bad for training a model: copies of one photo? (a) good for training (b) bad for training
29. 29.True or false: “new data for testing” is good for training a model. (a) False (b) True
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.Which of these is good for training a model? (a) many varied examples (b) only one kind of example (c) labels added at random (d) very few examples
32. 32.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “not spam”. (a) False (b) True
33. 33.Which of these is bad for training a model? (a) clear, sharp examples (b) correct labels (c) labels added at random (d) photos in many lights
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) a song about dogs (d) many labelled photos
35. 35.True or false: the message “You won a free phone! Click now!” should be labelled “not spam”. (a) True (b) False
36. 36.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will be perfect (b) it will turn yellow (c) it will shut down (d) it may get it wrong
37. 37.🔍 Which is the odd one out? (a) clear, sharp examples (b) checking labels twice (c) very few examples (d) many varied examples
38. 38.🏷️ 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
39. 39.🏷️ What is a “label” in machine learning? (a) the right answer tag (b) the price (c) the font size (d) a sticker on a laptop
40. 40.True or false: “blurry, unclear photos” is good for training a model. (a) False (b) True

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