Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 348 · 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 bad for training a model? (a) very few examples (b) examples of every type (c) correct labels (d) many varied examples
2. 2.True or false: “new data for testing” is bad for training a model. (a) True (b) False
3. 3.📚 Good or bad for training a model: very few examples? (a) bad for training (b) good for training
4. 4.🐶 To teach a model to spot dogs in photos, what do you give it? (a) a song about dogs (b) one single photo (c) a list of rules only (d) many labelled photos
5. 5.Which of these is good for training a model? (a) testing on training data (b) many varied examples (c) copies of one photo (d) only one kind of example
6. 6.True or false: “correct labels” is good for training a model. (a) False (b) True
7. 7.🏷️ 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
8. 8.True or false: “checking labels twice” is bad for training a model. (a) True (b) False
9. 9.🏷️ 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
10. 10.True or false: “wrong labels” is good for training a model. (a) False (b) True
11. 11.Which of these is bad for training a model? (a) many varied examples (b) checking labels twice (c) copies of one photo (d) correct labels
12. 12.True or false: the message “Science project groups are on the board” should be labelled “not spam”. (a) True (b) False
13. 13.Which of these is bad for training a model? (a) many varied examples (b) examples of every type (c) only one kind of example (d) correct labels
14. 14.True or false: “photos in many lights” is good for training a model. (a) False (b) True
15. 15.Which of these is good for training a model? (a) very few examples (b) blurry, unclear photos (c) labels added at random (d) checking labels twice
16. 16.🔍 Which is the odd one out? (a) very few examples (b) clear, sharp examples (c) photos in many lights (d) correct labels
17. 17.🏷️ 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
18. 18.📚 Usually, more good examples make a model… (a) change colour (b) forget everything (c) slower to switch on (d) better at its task
19. 19.Which of these is good for training a model? (a) clear, sharp examples (b) wrong labels (c) labels added at random (d) only one kind of example
20. 20.🔍 Which is the odd one out? (a) only one kind of example (b) wrong labels (c) clear, sharp examples (d) labels added at random
21. 21.True or false: the message “Happy birthday! See you at lunch” should be labelled “not spam”. (a) True (b) False
22. 22.📚 Good or bad for training a model: correct labels? (a) bad for training (b) good for training
23. 23.📚 Good or bad for training a model: many varied examples? (a) good for training (b) bad for training
24. 24.🏷️ 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
25. 25.📚 Good or bad for training a model: photos in many lights? (a) bad for training (b) good for training
26. 26.🏷️ What is a “label” in machine learning? (a) the font size (b) a sticker on a laptop (c) the price (d) the right answer tag
27. 27.Which of these is bad for training a model? (a) correct labels (b) new data for testing (c) wrong labels (d) photos in many lights
28. 28.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “not spam”. (a) True (b) False
29. 29.True or false: “only one kind of example” is good for training a model. (a) False (b) True
30. 30.🔍 Which is the odd one out? (a) wrong labels (b) labels added at random (c) only one kind of example (d) correct labels
31. 31.True or false: the message “Last chance! Free gift card inside” should be labelled “spam”. (a) True (b) False
32. 32.True or false: the message “Your library book is due on Monday” should be labelled “not spam”. (a) True (b) False
33. 33.True or false: “many varied examples” is bad for training a model. (a) True (b) False
34. 34.Which of these is bad for training a model? (a) blurry, unclear photos (b) many varied examples (c) new data for testing (d) correct labels
35. 35.🔍 Which is the odd one out? (a) photos in many lights (b) wrong labels (c) new data for testing (d) examples of every type
36. 36.True or false: the message “Share your OTP to get cashback” should be labelled “spam”. (a) True (b) False
37. 37.🏷️ 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
38. 38.Which of these is good for training a model? (a) very few examples (b) copies of one photo (c) labels added at random (d) examples of every type
39. 39.True or false: “clear, sharp examples” is bad for training a model. (a) True (b) False
40. 40.True or false: “copies of one photo” is good for training a model. (a) False (b) True

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