Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 396 · 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 is the odd one out? (a) examples of every type (b) clear, sharp examples (c) new data for testing (d) copies of one photo
2. 2.📚 Good or bad for training a model: correct labels? (a) bad for training (b) good for training
3. 3.🔍 Which is the odd one out? (a) many varied examples (b) labels added at random (c) new data for testing (d) examples of every type
4. 4.Which of these is bad for training a model? (a) wrong labels (b) examples of every type (c) photos in many lights (d) new data for testing
5. 5.🏷️ 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) spam (b) not spam
6. 6.🧠 Machine learning is a way for computers to… (a) charge faster (b) print pages (c) learn from data (d) clean screens
7. 7.True or false: “blurry, unclear photos” is bad for training a model. (a) True (b) False
8. 8.True or false: the message “You won a free phone! Click now!” should be labelled “not spam”. (a) True (b) False
9. 9.True or false: the message “Last chance! Free gift card inside” should be labelled “not spam”. (a) True (b) False
10. 10.Which of these is good for training a model? (a) photos in many lights (b) copies of one photo (c) wrong labels (d) very few examples
11. 11.True or false: “very few examples” is good for training a model. (a) True (b) False
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) spam (b) not spam
13. 13.Which of these is bad for training a model? (a) many varied examples (b) examples of every type (c) very few examples (d) photos in many lights
14. 14.True or false: the message “Share your OTP to get cashback” should be labelled “not spam”. (a) False (b) True
15. 15.🔍 Which is the odd one out? (a) new data for testing (b) many varied examples (c) blurry, unclear photos (d) examples of every type
16. 16.🔍 Which is the odd one out? (a) examples of every type (b) new data for testing (c) wrong labels (d) checking labels twice
17. 17.🔍 Which is the odd one out? (a) correct labels (b) only one kind of example (c) examples of every type (d) many varied examples
18. 18.True or false: “many varied examples” is bad for training a model. (a) False (b) True
19. 19.True or false: “new data for testing” is good for training a model. (a) False (b) True
20. 20.🔍 Which is the odd one out? (a) blurry, unclear photos (b) only one kind of example (c) copies of one photo (d) examples of every type
21. 21.True or false: the message “Send your password to claim a prize” should be labelled “spam”. (a) False (b) True
22. 22.🏷️ 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
23. 23.True or false: “very few examples” is bad for training a model. (a) True (b) False
24. 24.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will shut down (b) it will turn yellow (c) it may get it wrong (d) it will be perfect
25. 25.Which of these is good for training a model? (a) copies of one photo (b) testing on training data (c) labels added at random (d) examples of every type
26. 26.True or false: “testing on training data” is bad for training a model. (a) True (b) False
27. 27.True or false: “blurry, unclear photos” is good for training a model. (a) True (b) False
28. 28.🔍 Which is the odd one out? (a) testing on training data (b) very few examples (c) blurry, unclear photos (d) many varied examples
29. 29.Which of these is good for training a model? (a) checking labels twice (b) very few examples (c) blurry, unclear photos (d) only one kind of example
30. 30.True or false: “many varied examples” is good for training a model. (a) False (b) True
31. 31.📚 Good or bad for training a model: very few examples? (a) good for training (b) bad for training
32. 32.Which of these is good for training a model? (a) new data for testing (b) very few examples (c) labels added at random (d) blurry, unclear photos
33. 33.📚 Good or bad for training a model: many varied examples? (a) bad for training (b) good for training
34. 34.Which of these is bad for training a model? (a) clear, sharp examples (b) copies of one photo (c) new data for testing (d) many varied examples
35. 35.Which of these is bad for training a model? (a) new data for testing (b) labels added at random (c) examples of every type (d) checking labels twice
36. 36.True or false: “wrong labels” is bad for training a model. (a) True (b) False
37. 37.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “You won a free phone! Click now!” (a) not spam (b) spam
38. 38.🏷️ 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
39. 39.🔍 Which is the odd one out? (a) testing on training data (b) very few examples (c) labels added at random (d) new data for testing
40. 40.True or false: the message “Happy birthday! See you at lunch” should be labelled “spam”. (a) False (b) True

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