Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 358 · 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 good for training a model? (a) blurry, unclear photos (b) testing on training data (c) wrong labels (d) photos in many lights
2. 2.📚 Good or bad for training a model: many varied examples? (a) good for training (b) bad for training
3. 3.📚 Good or bad for training a model: blurry, unclear photos? (a) bad for training (b) good for training
4. 4.True or false: “checking labels twice” is good for training a model. (a) False (b) True
5. 5.Which of these is bad for training a model? (a) new data for testing (b) clear, sharp examples (c) many varied examples (d) blurry, unclear photos
6. 6.🧠 Machine learning is a way for computers to… (a) learn from data (b) print pages (c) clean screens (d) charge faster
7. 7.Which of these is bad for training a model? (a) many varied examples (b) clear, sharp examples (c) photos in many lights (d) very few examples
8. 8.True or false: the message “Happy birthday! See you at lunch” should be labelled “not spam”. (a) False (b) True
9. 9.Which of these is bad for training a model? (a) many varied examples (b) photos in many lights (c) testing on training data (d) checking labels twice
10. 10.🥭 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 be perfect (d) it will turn yellow
11. 11.🏷️ What is a “label” in machine learning? (a) the font size (b) a sticker on a laptop (c) the right answer tag (d) the price
12. 12.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “not spam”. (a) False (b) True
13. 13.🔍 Which is the odd one out? (a) labels added at random (b) correct labels (c) very few examples (d) copies of one photo
14. 14.🏷️ 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
15. 15.📚 Good or bad for training a model: copies of one photo? (a) bad for training (b) good for training
16. 16.📚 Good or bad for training a model: checking labels twice? (a) good for training (b) bad for training
17. 17.True or false: “only one kind of example” is bad for training a model. (a) False (b) True
18. 18.Which of these is good for training a model? (a) testing on training data (b) copies of one photo (c) labels added at random (d) many varied examples
19. 19.📚 Good or bad for training a model: new data for testing? (a) good for training (b) bad for training
20. 20.🏷️ 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
21. 21.True or false: “very few examples” is good for training a model. (a) False (b) True
22. 22.🔍 Which is the odd one out? (a) many varied examples (b) examples of every type (c) very few examples (d) clear, sharp examples
23. 23.Which of these is good for training a model? (a) new data for testing (b) very few examples (c) copies of one photo (d) wrong labels
24. 24.Which of these is good for training a model? (a) clear, sharp examples (b) very few examples (c) labels added at random (d) wrong labels
25. 25.🏷️ 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
26. 26.True or false: “new data for testing” is bad for training a model. (a) True (b) False
27. 27.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “not spam”. (a) False (b) True
28. 28.True or false: the message “Send your password to claim a prize” should be labelled “not spam”. (a) True (b) False
29. 29.🏷️ 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
30. 30.Which of these is bad for training a model? (a) only one kind of example (b) new data for testing (c) clear, sharp examples (d) examples of every type
31. 31.Which of these is good for training a model? (a) blurry, unclear photos (b) wrong labels (c) only one kind of example (d) checking labels twice
32. 32.🔍 Which is the odd one out? (a) clear, sharp examples (b) many varied examples (c) labels added at random (d) photos in many lights
33. 33.True or false: “labels added at random” is good for training a model. (a) True (b) False
34. 34.True or false: the message “Send your password to claim a prize” should be labelled “spam”. (a) False (b) True
35. 35.🔍 Which is the odd one out? (a) labels added at random (b) only one kind of example (c) examples of every type (d) testing on training data
36. 36.📚 Good or bad for training a model: testing on training data? (a) good for training (b) bad for training
37. 37.True or false: “copies of one photo” is good for training a model. (a) True (b) False
38. 38.True or false: “photos in many lights” is bad for training a model. (a) False (b) True
39. 39.Which of these is good for training a model? (a) testing on training data (b) examples of every type (c) blurry, unclear photos (d) copies of one photo
40. 40.True or false: “labels added at random” is bad for training a model. (a) True (b) False

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