Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 330 · 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.Which of these is bad for training a model? (a) copies of one photo (b) examples of every type (c) correct labels (d) photos in many lights
2. 2.🏷️ 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
3. 3.True or false: “photos in many lights” is good for training a model. (a) True (b) False
4. 4.🧠 Machine learning is a way for computers to… (a) charge faster (b) print pages (c) learn from data (d) clean screens
5. 5.🥭 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
6. 6.True or false: the message “You won a free phone! Click now!” should be labelled “not spam”. (a) True (b) False
7. 7.🔍 Which is the odd one out? (a) new data for testing (b) photos in many lights (c) correct labels (d) blurry, unclear photos
8. 8.🏷️ 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
9. 9.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Science project groups are on the board” (a) spam (b) not spam
10. 10.True or false: “only one kind of example” is bad for training a model. (a) False (b) True
11. 11.True or false: the message “Send your password to claim a prize” should be labelled “not spam”. (a) True (b) False
12. 12.📚 Good or bad for training a model: photos in many lights? (a) good for training (b) bad for training
13. 13.🔍 Which is the odd one out? (a) wrong labels (b) very few examples (c) checking labels twice (d) testing on training data
14. 14.True or false: the message “You won a free phone! Click now!” should be labelled “spam”. (a) False (b) True
15. 15.🔍 Which is the odd one out? (a) blurry, unclear photos (b) copies of one photo (c) only one kind of example (d) many varied examples
16. 16.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Match practice moved to 5 pm” (a) spam (b) not spam
17. 17.Which of these is good for training a model? (a) wrong labels (b) very few examples (c) labels added at random (d) many varied examples
18. 18.🔍 Which is the odd one out? (a) correct labels (b) photos in many lights (c) new data for testing (d) copies of one photo
19. 19.Which of these is good for training a model? (a) very few examples (b) copies of one photo (c) photos in many lights (d) only one kind of example
20. 20.🐶 To teach a model to spot dogs in photos, what do you give it? (a) one single photo (b) a song about dogs (c) many labelled photos (d) a list of rules only
21. 21.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “not spam”. (a) False (b) True
22. 22.Which of these is good for training a model? (a) very few examples (b) copies of one photo (c) wrong labels (d) clear, sharp examples
23. 23.📚 Good or bad for training a model: new data for testing? (a) bad for training (b) good for training
24. 24.📚 Good or bad for training a model: testing on training data? (a) bad for training (b) good for training
25. 25.Which of these is bad for training a model? (a) labels added at random (b) many varied examples (c) checking labels twice (d) new data for testing
26. 26.📚 Good or bad for training a model: very few examples? (a) good for training (b) bad for training
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.📚 Good or bad for training a model: clear, sharp examples? (a) bad for training (b) good for training
29. 29.🏷️ 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
30. 30.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Send your password to claim a prize” (a) not spam (b) spam
31. 31.🏷️ 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
32. 32.📚 Good or bad for training a model: wrong labels? (a) good for training (b) bad for training
33. 33.Which of these is bad for training a model? (a) blurry, unclear photos (b) checking labels twice (c) examples of every type (d) many varied examples
34. 34.🏷️ 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
35. 35.True or false: “photos in many lights” is bad for training a model. (a) False (b) True
36. 36.📚 Good or bad for training a model: blurry, unclear photos? (a) good for training (b) bad for training
37. 37.Which of these is bad for training a model? (a) testing on training data (b) clear, sharp examples (c) examples of every type (d) many varied examples
38. 38.🔍 Which is the odd one out? (a) blurry, unclear photos (b) examples of every type (c) testing on training data (d) very few examples
39. 39.Which of these is good for training a model? (a) labels added at random (b) copies of one photo (c) only one kind of example (d) correct labels
40. 40.True or false: “correct labels” is bad for training a model. (a) True (b) False

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