Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 429 · 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? “The class picnic is on Friday at 8 am” (a) not spam (b) spam
2. 2.📚 Good or bad for training a model: copies of one photo? (a) bad for training (b) good for training
3. 3.📚 Good or bad for training a model: clear, sharp examples? (a) good for training (b) bad for training
4. 4.True or false: “correct labels” is bad for training a model. (a) True (b) False
5. 5.True or false: “labels added at random” is bad for training a model. (a) False (b) True
6. 6.📚 Good or bad for training a model: correct labels? (a) good for training (b) bad for training
7. 7.🔍 Which is the odd one out? (a) many varied examples (b) photos in many lights (c) very few examples (d) new data for testing
8. 8.Which of these is bad for training a model? (a) testing on training data (b) many varied examples (c) checking labels twice (d) new data for testing
9. 9.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your account is locked, pay ₹99 now” (a) spam (b) not spam
10. 10.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “not spam”. (a) False (b) True
11. 11.Which of these is good for training a model? (a) labels added at random (b) blurry, unclear photos (c) photos in many lights (d) wrong labels
12. 12.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Earn ₹50,000 a day from home!!!” (a) not spam (b) spam
13. 13.📚 Good or bad for training a model: very few examples? (a) good for training (b) bad for training
14. 14.Which of these is bad for training a model? (a) many varied examples (b) examples of every type (c) copies of one photo (d) checking labels twice
15. 15.🏷️ 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
16. 16.Which of these is bad for training a model? (a) examples of every type (b) new data for testing (c) checking labels twice (d) labels added at random
17. 17.🔍 Which is the odd one out? (a) examples of every type (b) clear, sharp examples (c) photos in many lights (d) copies of one photo
18. 18.📚 Good or bad for training a model: checking labels twice? (a) good for training (b) bad for training
19. 19.Which of these is good for training a model? (a) many varied examples (b) testing on training data (c) labels added at random (d) only one kind of example
20. 20.🧠 Machine learning is a way for computers to… (a) print pages (b) clean screens (c) learn from data (d) charge faster
21. 21.📚 Good or bad for training a model: many varied examples? (a) good for training (b) bad for training
22. 22.Which of these is bad for training a model? (a) checking labels twice (b) new data for testing (c) clear, sharp examples (d) very few examples
23. 23.🏷️ 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
24. 24.🐶 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
25. 25.True or false: “new data for testing” is bad for training a model. (a) False (b) True
26. 26.True or false: the message “Happy birthday! See you at lunch” should be labelled “spam”. (a) False (b) True
27. 27.True or false: “blurry, unclear photos” is good for training a model. (a) False (b) True
28. 28.🔍 Which is the odd one out? (a) very few examples (b) wrong labels (c) labels added at random (d) many varied examples
29. 29.Which of these is good for training a model? (a) wrong labels (b) blurry, unclear photos (c) testing on training data (d) new data for testing
30. 30.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “spam”. (a) True (b) False
31. 31.Which of these is good for training a model? (a) wrong labels (b) blurry, unclear photos (c) only one kind of example (d) checking labels twice
32. 32.🔍 Which is the odd one out? (a) new data for testing (b) clear, sharp examples (c) checking labels twice (d) blurry, unclear photos
33. 33.True or false: “photos in many lights” is good for training a model. (a) True (b) False
34. 34.True or false: “testing on training data” is good for training a model. (a) False (b) True
35. 35.📚 Good or bad for training a model: only one kind of example? (a) bad for training (b) good for training
36. 36.🔍 Which is the odd one out? (a) only one kind of example (b) very few examples (c) blurry, unclear photos (d) correct labels
37. 37.Which of these is good for training a model? (a) blurry, unclear photos (b) very few examples (c) wrong labels (d) correct labels
38. 38.🔍 Which is the odd one out? (a) clear, sharp examples (b) checking labels twice (c) correct labels (d) only one kind of example
39. 39.True or false: the message “You won a free phone! Click now!” should be labelled “not spam”. (a) True (b) False
40. 40.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it may get it wrong (b) it will turn yellow (c) it will be perfect (d) it will shut down

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