Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 67 · 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.🐶 To teach a model to spot dogs in photos, what do you give it? (a) a list of rules only (b) one single photo (c) many labelled photos (d) a song about dogs
2. 2.True or false: the message “Last chance! Free gift card inside” should be labelled “spam”. (a) False (b) True
3. 3.True or false: “examples of every type” is bad for training a model. (a) False (b) True
4. 4.🔍 Which is the odd one out? (a) examples of every type (b) wrong labels (c) many varied examples (d) clear, sharp examples
5. 5.📚 Good or bad for training a model: very few examples? (a) bad for training (b) good for training
6. 6.🏷️ 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
7. 7.Which of these is good for training a model? (a) only one kind of example (b) very few examples (c) copies of one photo (d) clear, sharp examples
8. 8.📚 Usually, more good examples make a model… (a) change colour (b) slower to switch on (c) forget everything (d) better at its task
9. 9.📚 Good or bad for training a model: new data for testing? (a) bad for training (b) good for training
10. 10.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “spam”. (a) True (b) False
11. 11.True or false: the message “Match practice moved to 5 pm” should be labelled “spam”. (a) False (b) True
12. 12.🧠 Machine learning is a way for computers to… (a) learn from data (b) clean screens (c) charge faster (d) print pages
13. 13.Which of these is bad for training a model? (a) photos in many lights (b) checking labels twice (c) wrong labels (d) new data for testing
14. 14.🔍 Which is the odd one out? (a) very few examples (b) copies of one photo (c) blurry, unclear photos (d) new data for testing
15. 15.📚 Good or bad for training a model: labels added at random? (a) good for training (b) bad for training
16. 16.📚 Good or bad for training a model: only one kind of example? (a) good for training (b) bad for training
17. 17.📚 Good or bad for training a model: blurry, unclear photos? (a) bad for training (b) good for training
18. 18.📚 Good or bad for training a model: correct labels? (a) bad for training (b) good for training
19. 19.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your account is locked, pay ₹99 now” (a) not spam (b) spam
20. 20.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will be perfect (b) it will shut down (c) it will turn yellow (d) it may get it wrong
21. 21.📚 Good or bad for training a model: checking labels twice? (a) good for training (b) bad for training
22. 22.🔍 Which is the odd one out? (a) clear, sharp examples (b) correct labels (c) photos in many lights (d) copies of one photo
23. 23.True or false: the message “Science project groups are on the board” should be labelled “spam”. (a) True (b) False
24. 24.True or false: “blurry, unclear photos” is bad for training a model. (a) False (b) True
25. 25.🏷️ What is a “label” in machine learning? (a) a sticker on a laptop (b) the font size (c) the price (d) the right answer tag
26. 26.🏷️ 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) not spam (b) spam
27. 27.True or false: “only one kind of example” is bad for training a model. (a) True (b) False
28. 28.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Happy birthday! See you at lunch” (a) not spam (b) spam
29. 29.Which of these is good for training a model? (a) wrong labels (b) labels added at random (c) photos in many lights (d) only one kind of example
30. 30.True or false: “correct labels” is bad for training a model. (a) False (b) True
31. 31.True or false: “very few examples” is bad for training a model. (a) True (b) False
32. 32.True or false: “labels added at random” is good for training a model. (a) False (b) True
33. 33.True or false: the message “Last chance! Free gift card inside” should be labelled “not spam”. (a) True (b) False
34. 34.Which of these is bad for training a model? (a) new data for testing (b) examples of every type (c) clear, sharp examples (d) blurry, unclear photos
35. 35.📚 Good or bad for training a model: copies of one photo? (a) good for training (b) bad for training
36. 36.🏷️ 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
37. 37.True or false: the message “Match practice moved to 5 pm” should be labelled “not spam”. (a) True (b) False
38. 38.📚 Good or bad for training a model: examples of every type? (a) good for training (b) bad for training
39. 39.True or false: the message “Share your OTP to get cashback” should be labelled “not spam”. (a) False (b) True
40. 40.🔍 Which is the odd one out? (a) very few examples (b) copies of one photo (c) blurry, unclear photos (d) examples of every type

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