Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 446 · 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: the message “Science project groups are on the board” should be labelled “not spam”. (a) True (b) False
2. 2.📚 Good or bad for training a model: copies of one photo? (a) bad for training (b) good for training
3. 3.Which of these is bad for training a model? (a) clear, sharp examples (b) photos in many lights (c) testing on training data (d) examples of every type
4. 4.True or false: “photos in many lights” is good for training a model. (a) False (b) True
5. 5.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Send your password to claim a prize” (a) spam (b) not spam
6. 6.True or false: the message “Last chance! Free gift card inside” should be labelled “not spam”. (a) False (b) True
7. 7.🔍 Which is the odd one out? (a) new data for testing (b) many varied examples (c) photos in many lights (d) labels added at random
8. 8.📚 Good or bad for training a model: many varied examples? (a) good for training (b) bad for training
9. 9.Which of these is bad for training a model? (a) many varied examples (b) photos in many lights (c) new data for testing (d) very few examples
10. 10.True or false: the message “Share your OTP to get cashback” should be labelled “spam”. (a) False (b) True
11. 11.📚 Good or bad for training a model: blurry, unclear photos? (a) bad for training (b) good for training
12. 12.🔍 Which is the odd one out? (a) new data for testing (b) photos in many lights (c) blurry, unclear photos (d) correct labels
13. 13.📚 Good or bad for training a model: correct labels? (a) good for training (b) bad for training
14. 14.Which of these is good for training a model? (a) very few examples (b) blurry, unclear photos (c) copies of one photo (d) examples of every type
15. 15.Which of these is good for training a model? (a) wrong labels (b) blurry, unclear photos (c) new data for testing (d) copies of one photo
16. 16.🏷️ What is a “label” in machine learning? (a) the font size (b) the right answer tag (c) the price (d) a sticker on a laptop
17. 17.True or false: “checking labels twice” is bad for training a model. (a) True (b) False
18. 18.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will turn yellow (b) it will shut down (c) it will be perfect (d) it may get it wrong
19. 19.🔍 Which is the odd one out? (a) testing on training data (b) copies of one photo (c) clear, sharp examples (d) labels added at random
20. 20.Which of these is good for training a model? (a) wrong labels (b) labels added at random (c) clear, sharp examples (d) only one kind of example
21. 21.Which of these is bad for training a model? (a) photos in many lights (b) labels added at random (c) many varied examples (d) clear, sharp examples
22. 22.Which of these is good for training a model? (a) testing on training data (b) wrong labels (c) correct labels (d) blurry, unclear photos
23. 23.🔍 Which is the odd one out? (a) blurry, unclear photos (b) copies of one photo (c) photos in many lights (d) very few examples
24. 24.🏷️ 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
25. 25.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “spam”. (a) False (b) True
26. 26.📚 Good or bad for training a model: very few examples? (a) bad for training (b) good for training
27. 27.📚 Good or bad for training a model: photos in many lights? (a) bad for training (b) good for training
28. 28.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “spam”. (a) False (b) True
29. 29.True or false: the message “Send your password to claim a prize” should be labelled “spam”. (a) True (b) False
30. 30.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Happy birthday! See you at lunch” (a) spam (b) not spam
31. 31.True or false: the message “Share your OTP to get cashback” should be labelled “not spam”. (a) True (b) False
32. 32.🔍 Which is the odd one out? (a) many varied examples (b) clear, sharp examples (c) wrong labels (d) examples of every type
33. 33.Which of these is good for training a model? (a) very few examples (b) wrong labels (c) checking labels twice (d) blurry, unclear photos
34. 34.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “not spam”. (a) True (b) False
35. 35.🔍 Which is the odd one out? (a) clear, sharp examples (b) copies of one photo (c) photos in many lights (d) new data for testing
36. 36.🐶 To teach a model to spot dogs in photos, what do you give it? (a) many labelled photos (b) a song about dogs (c) one single photo (d) a list of rules only
37. 37.True or false: “testing on training data” is bad for training a model. (a) True (b) False
38. 38.🏷️ 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
39. 39.Which of these is bad for training a model? (a) wrong labels (b) examples of every type (c) clear, sharp examples (d) many varied examples
40. 40.🏷️ 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

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