Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 116 · 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: “correct labels” is good for training a model. (a) False (b) True
2. 2.🔍 Which is the odd one out? (a) wrong labels (b) only one kind of example (c) photos in many lights (d) blurry, unclear photos
3. 3.📚 Good or bad for training a model: photos in many lights? (a) good for training (b) bad for training
4. 4.🏷️ 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
5. 5.🏷️ 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
6. 6.Which of these is good for training a model? (a) very few examples (b) wrong labels (c) checking labels twice (d) only one kind of example
7. 7.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your account is locked, pay ₹99 now” (a) spam (b) not spam
8. 8.🧠 Machine learning is a way for computers to… (a) charge faster (b) print pages (c) clean screens (d) learn from data
9. 9.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will be perfect (b) it may get it wrong (c) it will shut down (d) it will turn yellow
10. 10.🔍 Which is the odd one out? (a) checking labels twice (b) very few examples (c) correct labels (d) many varied examples
11. 11.🔍 Which is the odd one out? (a) labels added at random (b) very few examples (c) new data for testing (d) testing on training data
12. 12.True or false: “examples of every type” is bad for training a model. (a) False (b) True
13. 13.🔍 Which is the odd one out? (a) clear, sharp examples (b) many varied examples (c) correct labels (d) only one kind of example
14. 14.🏷️ 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
15. 15.True or false: the message “You won a free phone! Click now!” should be labelled “spam”. (a) False (b) True
16. 16.Which of these is good for training a model? (a) correct labels (b) testing on training data (c) wrong labels (d) blurry, unclear photos
17. 17.True or false: “photos in many lights” is bad for training a model. (a) True (b) False
18. 18.🐶 To teach a model to spot dogs in photos, what do you give it? (a) one single photo (b) a song about dogs (c) many labelled photos (d) a list of rules only
19. 19.True or false: the message “Happy birthday! See you at lunch” should be labelled “spam”. (a) True (b) False
20. 20.Which of these is good for training a model? (a) labels added at random (b) many varied examples (c) blurry, unclear photos (d) copies of one photo
21. 21.📚 Good or bad for training a model: many varied examples? (a) good for training (b) bad for training
22. 22.📚 Good or bad for training a model: correct labels? (a) bad for training (b) good for training
23. 23.🏷️ 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
24. 24.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “spam”. (a) False (b) True
25. 25.📚 Good or bad for training a model: wrong labels? (a) bad for training (b) good for training
26. 26.True or false: “wrong labels” is good for training a model. (a) True (b) False
27. 27.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “not spam”. (a) True (b) False
28. 28.Which of these is bad for training a model? (a) checking labels twice (b) photos in many lights (c) correct labels (d) blurry, unclear photos
29. 29.📚 Good or bad for training a model: only one kind of example? (a) good for training (b) bad for training
30. 30.📚 Good or bad for training a model: examples of every type? (a) bad for training (b) good for training
31. 31.Which of these is good for training a model? (a) copies of one photo (b) labels added at random (c) examples of every type (d) only one kind of example
32. 32.Which of these is good for training a model? (a) labels added at random (b) only one kind of example (c) new data for testing (d) very few examples
33. 33.📚 Good or bad for training a model: testing on training data? (a) good for training (b) bad for training
34. 34.True or false: “new data for testing” is bad for training a model. (a) True (b) False
35. 35.Which of these is bad for training a model? (a) correct labels (b) very few examples (c) examples of every type (d) many varied examples
36. 36.🏷️ What is a “label” in machine learning? (a) the price (b) a sticker on a laptop (c) the font size (d) the right answer tag
37. 37.True or false: “blurry, unclear photos” is bad for training a model. (a) False (b) True
38. 38.True or false: “labels added at random” is good for training a model. (a) True (b) False
39. 39.True or false: “copies of one photo” is bad for training a model. (a) True (b) False
40. 40.🔍 Which is the odd one out? (a) very few examples (b) blurry, unclear photos (c) testing on training data (d) examples of every type

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