Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 591 · 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.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Earn ₹50,000 a day from home!!!” (a) not spam (b) spam
2. 2.📚 Good or bad for training a model: clear, sharp examples? (a) good for training (b) bad for training
3. 3.True or false: “photos in many lights” is bad for training a model. (a) True (b) False
4. 4.🔍 Which is the odd one out? (a) clear, sharp examples (b) checking labels twice (c) wrong labels (d) photos in many lights
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.True or false: “copies of one photo” is bad for training a model. (a) True (b) False
7. 7.🧠 Machine learning is a way for computers to… (a) print pages (b) charge faster (c) clean screens (d) learn from data
8. 8.Which of these is good for training a model? (a) blurry, unclear photos (b) many varied examples (c) labels added at random (d) copies of one photo
9. 9.Which of these is good for training a model? (a) wrong labels (b) examples of every type (c) only one kind of example (d) copies of one photo
10. 10.📚 Good or bad for training a model: labels added at random? (a) bad for training (b) good for training
11. 11.📚 Good or bad for training a model: checking labels twice? (a) good for training (b) bad for training
12. 12.🥭 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
13. 13.📚 Good or bad for training a model: very few examples? (a) good for training (b) bad for training
14. 14.🏷️ 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
15. 15.🔍 Which is the odd one out? (a) copies of one photo (b) testing on training data (c) examples of every type (d) very few examples
16. 16.True or false: “many varied examples” is good for training a model. (a) True (b) False
17. 17.True or false: the message “Science project groups are on the board” should be labelled “not spam”. (a) False (b) True
18. 18.🐶 To teach a model to spot dogs in photos, what do you give it? (a) a list of rules only (b) many labelled photos (c) one single photo (d) a song about dogs
19. 19.🏷️ What is a “label” in machine learning? (a) the price (b) a sticker on a laptop (c) the right answer tag (d) the font size
20. 20.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Science project groups are on the board” (a) spam (b) not spam
21. 21.Which of these is bad for training a model? (a) new data for testing (b) wrong labels (c) clear, sharp examples (d) checking labels twice
22. 22.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Share your OTP to get cashback” (a) spam (b) not spam
23. 23.Which of these is good for training a model? (a) very few examples (b) testing on training data (c) copies of one photo (d) clear, sharp examples
24. 24.📚 Good or bad for training a model: correct labels? (a) good for training (b) bad for training
25. 25.📚 Good or bad for training a model: copies of one photo? (a) bad for training (b) good for training
26. 26.Which of these is good for training a model? (a) copies of one photo (b) photos in many lights (c) testing on training data (d) blurry, unclear photos
27. 27.📚 Good or bad for training a model: blurry, unclear photos? (a) good for training (b) bad for training
28. 28.True or false: the message “Please buy milk on the way home” should be labelled “spam”. (a) True (b) False
29. 29.Which of these is good for training a model? (a) very few examples (b) testing on training data (c) correct labels (d) only one kind of example
30. 30.Which of these is good for training a model? (a) labels added at random (b) blurry, unclear photos (c) checking labels twice (d) testing on training data
31. 31.📚 Good or bad for training a model: wrong labels? (a) bad for training (b) good for training
32. 32.📚 Good or bad for training a model: new data for testing? (a) bad for training (b) good for training
33. 33.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “spam”. (a) False (b) True
34. 34.📚 Usually, more good examples make a model… (a) slower to switch on (b) better at its task (c) change colour (d) forget everything
35. 35.Which of these is good for training a model? (a) testing on training data (b) only one kind of example (c) blurry, unclear photos (d) new data for testing
36. 36.True or false: “new data for testing” 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) spam (b) not spam
38. 38.🔍 Which is the odd one out? (a) photos in many lights (b) new data for testing (c) examples of every type (d) labels added at random
39. 39.Which of these is bad for training a model? (a) correct labels (b) new data for testing (c) very few examples (d) clear, sharp examples
40. 40.Which of these is bad for training a model? (a) examples of every type (b) correct labels (c) only one kind of example (d) photos in many lights

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