Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 281 · 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: “photos in many lights” is good for training a model. (a) True (b) False
2. 2.🔍 Which is the odd one out? (a) photos in many lights (b) many varied examples (c) copies of one photo (d) examples of every type
3. 3.📚 Good or bad for training a model: testing on training data? (a) good for training (b) bad for training
4. 4.📚 Good or bad for training a model: photos in many lights? (a) good for training (b) bad for training
5. 5.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your account is locked, pay ₹99 now” (a) not spam (b) spam
6. 6.🔍 Which is the odd one out? (a) blurry, unclear photos (b) wrong labels (c) very few examples (d) clear, sharp examples
7. 7.🔍 Which is the odd one out? (a) many varied examples (b) labels added at random (c) clear, sharp examples (d) examples of every type
8. 8.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Last chance! Free gift card inside” (a) not spam (b) spam
9. 9.Which of these is good for training a model? (a) copies of one photo (b) only one kind of example (c) photos in many lights (d) labels added at random
10. 10.True or false: the message “You won a free phone! Click now!” should be labelled “not spam”. (a) False (b) True
11. 11.📚 Good or bad for training a model: copies of one photo? (a) good for training (b) bad for training
12. 12.True or false: “clear, sharp examples” is bad for training a model. (a) True (b) False
13. 13.🔍 Which is the odd one out? (a) copies of one photo (b) blurry, unclear photos (c) wrong labels (d) checking labels twice
14. 14.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “You won a free phone! Click now!” (a) spam (b) not spam
15. 15.True or false: “examples of every type” is bad for training a model. (a) True (b) False
16. 16.Which of these is bad for training a model? (a) very few examples (b) new data for testing (c) checking labels twice (d) many varied examples
17. 17.🔍 Which is the odd one out? (a) many varied examples (b) wrong labels (c) clear, sharp examples (d) checking labels twice
18. 18.🥭 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 turn yellow (d) it will be perfect
19. 19.True or false: the message “Send your password to claim a prize” should be labelled “spam”. (a) False (b) True
20. 20.📚 Good or bad for training a model: examples of every type? (a) bad for training (b) good for training
21. 21.📚 Good or bad for training a model: many varied examples? (a) bad for training (b) good for training
22. 22.📚 Good or bad for training a model: wrong labels? (a) good for training (b) bad for training
23. 23.🐶 To teach a model to spot dogs in photos, what do you give it? (a) one single photo (b) many labelled photos (c) a song about dogs (d) a list of rules only
24. 24.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “spam”. (a) True (b) False
25. 25.🏷️ 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
26. 26.🏷️ 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
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.📚 Good or bad for training a model: checking labels twice? (a) good for training (b) bad for training
29. 29.🔍 Which is the odd one out? (a) copies of one photo (b) wrong labels (c) new data for testing (d) only one kind of example
30. 30.True or false: the message “Share your OTP to get cashback” should be labelled “spam”. (a) True (b) False
31. 31.📚 Good or bad for training a model: labels added at random? (a) good for training (b) bad for training
32. 32.Which of these is good for training a model? (a) labels added at random (b) many varied examples (c) copies of one photo (d) testing on training data
33. 33.🧠 Machine learning is a way for computers to… (a) charge faster (b) learn from data (c) clean screens (d) print pages
34. 34.True or false: the message “Happy birthday! See you at lunch” should be labelled “spam”. (a) True (b) False
35. 35.🏷️ What is a “label” in machine learning? (a) a sticker on a laptop (b) the right answer tag (c) the price (d) the font size
36. 36.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “not spam”. (a) False (b) True
37. 37.🏷️ 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
38. 38.Which of these is bad for training a model? (a) wrong labels (b) examples of every type (c) correct labels (d) photos in many lights
39. 39.📚 Good or bad for training a model: new data for testing? (a) good for training (b) bad for training
40. 40.True or false: the message “Last chance! Free gift card inside” should be labelled “not spam”. (a) True (b) False

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