Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 242 · 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? “Earn ₹50,000 a day from home!!!” (a) spam (b) not spam
2. 2.📚 Good or bad for training a model: examples of every type? (a) bad for training (b) good for training
3. 3.🏷️ 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
4. 4.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Last chance! Free gift card inside” (a) spam (b) not spam
5. 5.📚 Good or bad for training a model: many varied examples? (a) good for training (b) bad for training
6. 6.Which of these is good for training a model? (a) blurry, unclear photos (b) examples of every type (c) only one kind of example (d) very few examples
7. 7.🏷️ What is a “label” in machine learning? (a) the right answer tag (b) a sticker on a laptop (c) the font size (d) the price
8. 8.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Please buy milk on the way home” (a) spam (b) not spam
9. 9.True or false: “labels added at random” is bad for training a model. (a) True (b) False
10. 10.📚 Usually, more good examples make a model… (a) forget everything (b) change colour (c) better at its task (d) slower to switch on
11. 11.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will shut down (b) it will be perfect (c) it will turn yellow (d) it may get it wrong
12. 12.📚 Good or bad for training a model: copies of one photo? (a) good for training (b) bad for training
13. 13.Which of these is good for training a model? (a) only one kind of example (b) correct labels (c) testing on training data (d) wrong labels
14. 14.📚 Good or bad for training a model: correct labels? (a) bad for training (b) good for training
15. 15.🏷️ 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
16. 16.🔍 Which is the odd one out? (a) testing on training data (b) blurry, unclear photos (c) labels added at random (d) correct labels
17. 17.Which of these is good for training a model? (a) very few examples (b) new data for testing (c) blurry, unclear photos (d) wrong labels
18. 18.📚 Good or bad for training a model: wrong labels? (a) good for training (b) bad for training
19. 19.True or false: “very few examples” is good for training a model. (a) False (b) True
20. 20.Which of these is bad for training a model? (a) new data for testing (b) correct labels (c) very few examples (d) many varied examples
21. 21.True or false: the message “Please buy milk on the way home” should be labelled “not spam”. (a) True (b) False
22. 22.True or false: “very few examples” is bad for training a model. (a) False (b) True
23. 23.Which of these is good for training a model? (a) labels added at random (b) very few examples (c) many varied examples (d) blurry, unclear photos
24. 24.True or false: “testing on training data” is bad for training a model. (a) True (b) False
25. 25.📚 Good or bad for training a model: testing on training data? (a) good for training (b) bad for training
26. 26.True or false: “wrong labels” is bad for training a model. (a) True (b) False
27. 27.True or false: the message “You won a free phone! Click now!” should be labelled “spam”. (a) True (b) False
28. 28.🏷️ 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
29. 29.📚 Good or bad for training a model: labels added at random? (a) bad for training (b) good for training
30. 30.🏷️ 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
31. 31.True or false: the message “Last chance! Free gift card inside” should be labelled “not spam”. (a) False (b) True
32. 32.📚 Good or bad for training a model: new data for testing? (a) bad for training (b) good for training
33. 33.Which of these is bad for training a model? (a) many varied examples (b) new data for testing (c) copies of one photo (d) examples of every type
34. 34.True or false: “testing on training data” is good for training a model. (a) True (b) False
35. 35.Which of these is bad for training a model? (a) photos in many lights (b) checking labels twice (c) wrong labels (d) clear, sharp examples
36. 36.🐶 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
37. 37.🧠 Machine learning is a way for computers to… (a) clean screens (b) charge faster (c) print pages (d) learn from data
38. 38.🔍 Which is the odd one out? (a) examples of every type (b) testing on training data (c) clear, sharp examples (d) checking labels twice
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) not spam (b) spam
40. 40.Which of these is good for training a model? (a) wrong labels (b) photos in many lights (c) labels added at random (d) blurry, unclear photos

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