Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 98 · 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: “testing on training data” is bad for training a model. (a) True (b) False
2. 2.🧠 Machine learning is a way for computers to… (a) charge faster (b) learn from data (c) clean screens (d) print pages
3. 3.Which of these is good for training a model? (a) wrong labels (b) testing on training data (c) labels added at random (d) new data for testing
4. 4.📚 Good or bad for training a model: correct labels? (a) bad for training (b) good for training
5. 5.True or false: the message “Please buy milk on the way home” should be labelled “spam”. (a) True (b) False
6. 6.🔍 Which is the odd one out? (a) correct labels (b) examples of every type (c) new data for testing (d) only one kind of example
7. 7.🔍 Which is the odd one out? (a) many varied examples (b) wrong labels (c) new data for testing (d) examples of every type
8. 8.📚 Good or bad for training a model: blurry, unclear photos? (a) good for training (b) bad for training
9. 9.True or false: “photos in many lights” is bad for training a model. (a) True (b) False
10. 10.🏷️ What is a “label” in machine learning? (a) the font size (b) a sticker on a laptop (c) the price (d) the right answer tag
11. 11.Which of these is good for training a model? (a) testing on training data (b) blurry, unclear photos (c) photos in many lights (d) labels added at random
12. 12.True or false: “copies of one photo” is bad for training a model. (a) True (b) False
13. 13.🥭 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 may get it wrong (d) it will shut down
14. 14.🐶 To teach a model to spot dogs in photos, what do you give it? (a) many labelled photos (b) a list of rules only (c) a song about dogs (d) one single photo
15. 15.True or false: “examples of every type” is good for training a model. (a) True (b) False
16. 16.🏷️ 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
17. 17.📚 Good or bad for training a model: new data for testing? (a) good for training (b) bad for training
18. 18.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “not spam”. (a) True (b) False
19. 19.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “not spam”. (a) True (b) False
20. 20.Which of these is bad for training a model? (a) correct labels (b) new data for testing (c) wrong labels (d) checking labels twice
21. 21.True or false: the message “You won a free phone! Click now!” should be labelled “spam”. (a) True (b) False
22. 22.🔍 Which is the odd one out? (a) wrong labels (b) blurry, unclear photos (c) only one kind of example (d) correct labels
23. 23.🔍 Which is the odd one out? (a) only one kind of example (b) blurry, unclear photos (c) clear, sharp examples (d) copies of one photo
24. 24.📚 Good or bad for training a model: photos in many lights? (a) good for training (b) bad for training
25. 25.Which of these is good for training a model? (a) many varied examples (b) blurry, unclear photos (c) very few examples (d) testing on training data
26. 26.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Science project groups are on the board” (a) not spam (b) spam
27. 27.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “not spam”. (a) False (b) True
28. 28.True or false: the message “Please buy milk on the way home” should be labelled “not spam”. (a) False (b) True
29. 29.True or false: the message “Your library book is due on Monday” should be labelled “spam”. (a) False (b) True
30. 30.🔍 Which is the odd one out? (a) testing on training data (b) many varied examples (c) correct labels (d) clear, sharp examples
31. 31.🔍 Which is the odd one out? (a) correct labels (b) new data for testing (c) blurry, unclear photos (d) clear, sharp examples
32. 32.📚 Good or bad for training a model: only one kind of example? (a) bad for training (b) good for training
33. 33.📚 Good or bad for training a model: testing on training data? (a) bad for training (b) good for training
34. 34.📚 Good or bad for training a model: very few examples? (a) bad for training (b) good for training
35. 35.📚 Good or bad for training a model: checking labels twice? (a) good for training (b) bad for training
36. 36.Which of these is good for training a model? (a) testing on training data (b) only one kind of example (c) correct labels (d) labels added at random
37. 37.True or false: the message “Send your password to claim a prize” should be labelled “not spam”. (a) True (b) False
38. 38.Which of these is good for training a model? (a) wrong labels (b) labels added at random (c) checking labels twice (d) blurry, unclear photos
39. 39.🔍 Which is the odd one out? (a) checking labels twice (b) clear, sharp examples (c) new data for testing (d) copies of one photo
40. 40.True or false: “examples of every type” is bad for training a model. (a) True (b) False

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