Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 118 · 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? “Happy birthday! See you at lunch” (a) not spam (b) spam
2. 2.📚 Good or bad for training a model: new data for testing? (a) bad for training (b) good for training
3. 3.True or false: “many varied examples” is bad for training a model. (a) True (b) False
4. 4.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will be perfect (b) it will shut down (c) it may get it wrong (d) it will turn yellow
5. 5.True or false: the message “Share your OTP to get cashback” should be labelled “not spam”. (a) True (b) False
6. 6.🐶 To teach a model to spot dogs in photos, what do you give it? (a) one single photo (b) a list of rules only (c) a song about dogs (d) many labelled photos
7. 7.Which of these is good for training a model? (a) labels added at random (b) correct labels (c) blurry, unclear photos (d) very few examples
8. 8.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “spam”. (a) True (b) False
9. 9.🧠 Machine learning is a way for computers to… (a) print pages (b) learn from data (c) charge faster (d) clean screens
10. 10.True or false: “checking labels twice” is bad for training a model. (a) True (b) False
11. 11.True or false: “blurry, unclear photos” is bad for training a model. (a) False (b) True
12. 12.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “not spam”. (a) False (b) True
13. 13.True or false: “wrong labels” is bad for training a model. (a) True (b) False
14. 14.🏷️ 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
15. 15.Which of these is good for training a model? (a) very few examples (b) clear, sharp examples (c) copies of one photo (d) only one kind of example
16. 16.True or false: “testing on training data” is bad for training a model. (a) True (b) False
17. 17.📚 Good or bad for training a model: correct labels? (a) bad for training (b) good for training
18. 18.True or false: the message “You won a free phone! Click now!” should be labelled “not spam”. (a) False (b) True
19. 19.Which of these is good for training a model? (a) blurry, unclear photos (b) very few examples (c) checking labels twice (d) wrong labels
20. 20.🏷️ 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
21. 21.Which of these is bad for training a model? (a) blurry, unclear photos (b) clear, sharp examples (c) many varied examples (d) checking labels twice
22. 22.🏷️ 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
23. 23.True or false: “new data for testing” is good for training a model. (a) True (b) False
24. 24.🔍 Which is the odd one out? (a) correct labels (b) photos in many lights (c) examples of every type (d) testing on training data
25. 25.📚 Usually, more good examples make a model… (a) forget everything (b) slower to switch on (c) better at its task (d) change colour
26. 26.True or false: “clear, sharp examples” is bad for training a model. (a) True (b) False
27. 27.Which of these is bad for training a model? (a) correct labels (b) many varied examples (c) checking labels twice (d) copies of one photo
28. 28.🔍 Which is the odd one out? (a) labels added at random (b) copies of one photo (c) blurry, unclear photos (d) photos in many lights
29. 29.🏷️ 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
30. 30.True or false: “only one kind of example” is bad for training a model. (a) True (b) False
31. 31.📚 Good or bad for training a model: very few examples? (a) good for training (b) bad for training
32. 32.📚 Good or bad for training a model: photos in many lights? (a) good for training (b) bad for training
33. 33.🔍 Which is the odd one out? (a) examples of every type (b) photos in many lights (c) new data for testing (d) wrong labels
34. 34.📚 Good or bad for training a model: labels added at random? (a) bad for training (b) good for training
35. 35.📚 Good or bad for training a model: many varied examples? (a) good for training (b) bad for training
36. 36.🔍 Which is the odd one out? (a) new data for testing (b) only one kind of example (c) very few examples (d) testing on training data
37. 37.Which of these is bad for training a model? (a) very few examples (b) new data for testing (c) checking labels twice (d) examples of every type
38. 38.📚 Good or bad for training a model: blurry, unclear photos? (a) good for training (b) bad for training
39. 39.🔍 Which is the odd one out? (a) many varied examples (b) checking labels twice (c) labels added at random (d) clear, sharp examples
40. 40.🔍 Which is the odd one out? (a) very few examples (b) examples of every type (c) copies of one photo (d) labels added at random

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