Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 492 · 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: “only one kind of example” is bad for training a model. (a) True (b) False
2. 2.True or false: “checking labels twice” is good for training a model. (a) True (b) False
3. 3.🏷️ What is a “label” in machine learning? (a) a sticker on a laptop (b) the right answer tag (c) the font size (d) the price
4. 4.🏷️ 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
5. 5.True or false: “examples of every type” is bad for training a model. (a) True (b) False
6. 6.True or false: the message “You won a free phone! Click now!” should be labelled “spam”. (a) False (b) True
7. 7.True or false: “blurry, unclear photos” is good for training a model. (a) False (b) True
8. 8.Which of these is good for training a model? (a) very few examples (b) correct labels (c) only one kind of example (d) blurry, unclear photos
9. 9.🐶 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
10. 10.True or false: “testing on training data” is bad for training a model. (a) False (b) True
11. 11.🔍 Which is the odd one out? (a) only one kind of example (b) wrong labels (c) very few examples (d) photos in many lights
12. 12.🔍 Which is the odd one out? (a) checking labels twice (b) copies of one photo (c) new data for testing (d) clear, sharp examples
13. 13.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Please buy milk on the way home” (a) spam (b) not spam
14. 14.🧠 Machine learning is a way for computers to… (a) clean screens (b) learn from data (c) print pages (d) charge faster
15. 15.True or false: the message “Happy birthday! See you at lunch” should be labelled “not spam”. (a) False (b) True
16. 16.True or false: “labels added at random” is bad for training a model. (a) True (b) False
17. 17.True or false: the message “Share your OTP to get cashback” should be labelled “not spam”. (a) True (b) False
18. 18.🏷️ 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) not spam (b) spam
19. 19.Which of these is good for training a model? (a) only one kind of example (b) very few examples (c) wrong labels (d) clear, sharp examples
20. 20.📚 Good or bad for training a model: labels added at random? (a) good for training (b) bad for training
21. 21.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Send your password to claim a prize” (a) not spam (b) spam
22. 22.Which of these is bad for training a model? (a) new data for testing (b) photos in many lights (c) copies of one photo (d) clear, sharp examples
23. 23.📚 Good or bad for training a model: correct labels? (a) good for training (b) bad for training
24. 24.📚 Good or bad for training a model: blurry, unclear photos? (a) bad for training (b) good for training
25. 25.📚 Good or bad for training a model: wrong labels? (a) bad for training (b) good for training
26. 26.True or false: the message “Your library book is due on Monday” should be labelled “spam”. (a) True (b) False
27. 27.True or false: “copies of one photo” is bad for training a model. (a) False (b) True
28. 28.🔍 Which is the odd one out? (a) many varied examples (b) testing on training data (c) correct labels (d) examples of every type
29. 29.True or false: the message “Share your OTP to get cashback” 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? “Earn ₹50,000 a day from home!!!” (a) spam (b) not spam
31. 31.📚 Good or bad for training a model: copies of one photo? (a) good for training (b) bad for training
32. 32.True or false: “correct labels” is bad for training a model. (a) True (b) False
33. 33.Which of these is good for training a model? (a) very few examples (b) blurry, unclear photos (c) wrong labels (d) many varied examples
34. 34.True or false: “wrong labels” is bad for training a model. (a) True (b) False
35. 35.📚 Good or bad for training a model: checking labels twice? (a) bad for training (b) good for training
36. 36.True or false: “examples of every type” is good 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.📚 Good or bad for training a model: clear, sharp examples? (a) good for training (b) bad for training
39. 39.Which of these is bad for training a model? (a) many varied examples (b) clear, sharp examples (c) checking labels twice (d) labels added at random
40. 40.🔍 Which is the odd one out? (a) new data for testing (b) wrong labels (c) clear, sharp examples (d) photos in many lights

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