Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 555 · 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 “Please buy milk on the way home” should be labelled “not spam”. (a) False (b) True
2. 2.📚 Good or bad for training a model: labels added at random? (a) good for training (b) bad for training
3. 3.Which of these is good for training a model? (a) new data for testing (b) blurry, unclear photos (c) wrong labels (d) only one kind of example
4. 4.Which of these is bad for training a model? (a) very few examples (b) many varied examples (c) clear, sharp examples (d) checking labels twice
5. 5.True or false: “examples of every type” is bad for training a model. (a) False (b) True
6. 6.🔍 Which is the odd one out? (a) photos in many lights (b) checking labels twice (c) labels added at random (d) examples of every type
7. 7.🏷️ 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
8. 8.Which of these is bad for training a model? (a) checking labels twice (b) copies of one photo (c) examples of every type (d) many varied examples
9. 9.True or false: the message “Share your OTP to get cashback” should be labelled “not spam”. (a) True (b) False
10. 10.True or false: “blurry, unclear photos” is bad for training a model. (a) True (b) False
11. 11.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will shut down (b) it may get it wrong (c) it will turn yellow (d) it will be perfect
12. 12.🐶 To teach a model to spot dogs in photos, what do you give it? (a) many labelled photos (b) one single photo (c) a list of rules only (d) a song about dogs
13. 13.True or false: the message “Share your OTP to get cashback” should be labelled “spam”. (a) True (b) False
14. 14.📚 Good or bad for training a model: very few examples? (a) bad for training (b) good for training
15. 15.🏷️ What is a “label” in machine learning? (a) the price (b) the font size (c) the right answer tag (d) a sticker on a laptop
16. 16.🔍 Which is the odd one out? (a) very few examples (b) checking labels twice (c) new data for testing (d) many varied examples
17. 17.True or false: “blurry, unclear photos” is good for training a model. (a) True (b) False
18. 18.Which of these is good for training a model? (a) wrong labels (b) very few examples (c) many varied examples (d) copies of one photo
19. 19.Which of these is bad for training a model? (a) clear, sharp examples (b) checking labels twice (c) photos in many lights (d) blurry, unclear photos
20. 20.True or false: “photos in many lights” is good for training a model. (a) True (b) False
21. 21.🏷️ 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
22. 22.📚 Usually, more good examples make a model… (a) forget everything (b) change colour (c) slower to switch on (d) better at its task
23. 23.Which of these is bad for training a model? (a) checking labels twice (b) many varied examples (c) labels added at random (d) photos in many lights
24. 24.📚 Good or bad for training a model: new data for testing? (a) good for training (b) bad for training
25. 25.🔍 Which is the odd one out? (a) testing on training data (b) labels added at random (c) many varied examples (d) only one kind of example
26. 26.🔍 Which is the odd one out? (a) wrong labels (b) correct labels (c) many varied examples (d) checking labels twice
27. 27.🏷️ 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
28. 28.🧠 Machine learning is a way for computers to… (a) print pages (b) learn from data (c) charge faster (d) clean screens
29. 29.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “not spam”. (a) False (b) True
30. 30.True or false: “clear, sharp examples” is good for training a model. (a) True (b) False
31. 31.🏷️ 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
32. 32.📚 Good or bad for training a model: checking labels twice? (a) bad for training (b) good for training
33. 33.🔍 Which is the odd one out? (a) testing on training data (b) checking labels twice (c) very few examples (d) copies of one photo
34. 34.🏷️ 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
35. 35.True or false: “testing on training data” is good for training a model. (a) True (b) False
36. 36.True or false: the message “Your library book is due on Monday” should be labelled “spam”. (a) True (b) False
37. 37.📚 Good or bad for training a model: clear, sharp examples? (a) bad for training (b) good for training
38. 38.True or false: “labels added at random” is good for training a model. (a) True (b) False
39. 39.🔍 Which is the odd one out? (a) correct labels (b) testing on training data (c) wrong labels (d) very few examples
40. 40.📚 Good or bad for training a model: photos in many lights? (a) bad for training (b) good for training

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