Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 146 · 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? “You won a free phone! Click now!” (a) spam (b) not spam
2. 2.Which of these is good for training a model? (a) copies of one photo (b) testing on training data (c) blurry, unclear photos (d) photos in many lights
3. 3.True or false: “correct labels” is bad for training a model. (a) False (b) True
4. 4.Which of these is bad for training a model? (a) many varied examples (b) labels added at random (c) correct labels (d) photos in many lights
5. 5.🔍 Which is the odd one out? (a) copies of one photo (b) wrong labels (c) clear, sharp examples (d) testing on training data
6. 6.True or false: “labels added at random” is good for training a model. (a) True (b) False
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) not spam (b) spam
8. 8.🧠 Machine learning is a way for computers to… (a) learn from data (b) charge faster (c) clean screens (d) print pages
9. 9.🔍 Which is the odd one out? (a) examples of every type (b) copies of one photo (c) labels added at random (d) blurry, unclear photos
10. 10.🔍 Which is the odd one out? (a) labels added at random (b) wrong labels (c) only one kind of example (d) checking labels twice
11. 11.🏷️ 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
12. 12.True or false: “only one kind of example” is good for training a model. (a) False (b) True
13. 13.Which of these is bad for training a model? (a) many varied examples (b) testing on training data (c) new data for testing (d) checking labels twice
14. 14.True or false: “testing on training data” is bad for training a model. (a) True (b) False
15. 15.True or false: the message “Science project groups are on the board” should be labelled “not spam”. (a) False (b) True
16. 16.📚 Usually, more good examples make a model… (a) better at its task (b) slower to switch on (c) change colour (d) forget everything
17. 17.Which of these is good for training a model? (a) wrong labels (b) blurry, unclear photos (c) correct labels (d) testing on training data
18. 18.True or false: the message “Happy birthday! See you at lunch” should be labelled “spam”. (a) True (b) False
19. 19.🔍 Which is the odd one out? (a) correct labels (b) copies of one photo (c) many varied examples (d) examples of every type
20. 20.True or false: “photos in many lights” is bad for training a model. (a) True (b) False
21. 21.📚 Good or bad for training a model: correct labels? (a) bad for training (b) good for training
22. 22.🥭 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
23. 23.Which of these is bad for training a model? (a) only one kind of example (b) clear, sharp examples (c) many varied examples (d) examples of every type
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.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Last chance! Free gift card inside” (a) spam (b) not spam
26. 26.🏷️ 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
27. 27.Which of these is bad for training a model? (a) checking labels twice (b) photos in many lights (c) clear, sharp examples (d) very few examples
28. 28.Which of these is good for training a model? (a) new data for testing (b) testing on training data (c) blurry, unclear photos (d) copies of one photo
29. 29.True or false: “checking labels twice” is good for training a model. (a) True (b) False
30. 30.📚 Good or bad for training a model: copies of one photo? (a) bad for training (b) good for training
31. 31.True or false: “only one kind of example” is bad for training a model. (a) False (b) True
32. 32.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Send your password to claim a prize” (a) spam (b) not spam
33. 33.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “spam”. (a) True (b) False
34. 34.📚 Good or bad for training a model: blurry, unclear photos? (a) good for training (b) bad for training
35. 35.Which of these is good for training a model? (a) testing on training data (b) wrong labels (c) copies of one photo (d) checking labels twice
36. 36.True or false: “very few examples” is bad for training a model. (a) False (b) True
37. 37.📚 Good or bad for training a model: new data for testing? (a) bad for training (b) good for training
38. 38.🔍 Which is the odd one out? (a) examples of every type (b) correct labels (c) only one kind of example (d) clear, sharp examples
39. 39.📚 Good or bad for training a model: photos in many lights? (a) bad for training (b) good for training
40. 40.🔍 Which is the odd one out? (a) copies of one photo (b) wrong labels (c) correct labels (d) only one kind of example

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