Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 299 · 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) many varied examples (b) new data for testing (c) labels added at random (d) photos in many lights
2. 2.📚 Good or bad for training a model: testing on training data? (a) good for training (b) bad for training
3. 3.Which of these is bad for training a model? (a) correct labels (b) examples of every type (c) only one kind of example (d) photos in many lights
4. 4.True or false: “testing on training data” is good for training a model. (a) False (b) True
5. 5.📚 Good or bad for training a model: only one kind of example? (a) bad for training (b) good for training
6. 6.True or false: “checking labels twice” 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? “You won a free phone! Click now!” (a) not spam (b) spam
8. 8.🔍 Which is the odd one out? (a) copies of one photo (b) testing on training data (c) correct labels (d) wrong labels
9. 9.True or false: the message “Science project groups are on the board” should be labelled “not spam”. (a) False (b) True
10. 10.🥭 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 will turn yellow (d) it may get it wrong
11. 11.🏷️ 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
12. 12.📚 Usually, more good examples make a model… (a) forget everything (b) better at its task (c) change colour (d) slower to switch on
13. 13.True or false: the message “Please buy milk on the way home” should be labelled “not spam”. (a) False (b) True
14. 14.🔍 Which is the odd one out? (a) testing on training data (b) copies of one photo (c) labels added at random (d) clear, sharp examples
15. 15.📚 Good or bad for training a model: very few examples? (a) bad for training (b) good for training
16. 16.True or false: the message “Your library book is due on Monday” should be labelled “not spam”. (a) False (b) True
17. 17.True or false: the message “Happy birthday! See you at lunch” should be labelled “not spam”. (a) True (b) False
18. 18.True or false: “wrong labels” is good for training a model. (a) True (b) False
19. 19.📚 Good or bad for training a model: new data for testing? (a) good for training (b) bad for training
20. 20.📚 Good or bad for training a model: correct labels? (a) bad for training (b) good for training
21. 21.🔍 Which is the odd one out? (a) blurry, unclear photos (b) checking labels twice (c) copies of one photo (d) very few examples
22. 22.🔍 Which is the odd one out? (a) copies of one photo (b) very few examples (c) new data for testing (d) wrong labels
23. 23.🔍 Which is the odd one out? (a) examples of every type (b) many varied examples (c) correct labels (d) copies of one photo
24. 24.Which of these is bad for training a model? (a) correct labels (b) clear, sharp examples (c) testing on training data (d) checking labels twice
25. 25.True or false: “checking labels twice” is bad for training a model. (a) False (b) True
26. 26.True or false: “clear, sharp examples” is bad for training a model. (a) True (b) False
27. 27.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “not spam”. (a) False (b) True
28. 28.True or false: the message “Share your OTP to get cashback” should be labelled “not spam”. (a) True (b) False
29. 29.📚 Good or bad for training a model: many varied examples? (a) bad for training (b) good for training
30. 30.🏷️ What is a “label” in machine learning? (a) the right answer tag (b) a sticker on a laptop (c) the font size (d) the price
31. 31.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Send your password to claim a prize” (a) not spam (b) spam
32. 32.True or false: “wrong labels” is bad for training a model. (a) True (b) False
33. 33.True or false: “blurry, unclear photos” is good for training a model. (a) True (b) False
34. 34.True or false: “photos in many lights” is bad for training a model. (a) False (b) True
35. 35.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “not spam”. (a) True (b) False
36. 36.🔍 Which is the odd one out? (a) testing on training data (b) only one kind of example (c) wrong labels (d) photos in many lights
37. 37.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Please buy milk on the way home” (a) not spam (b) spam
38. 38.🏷️ 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
39. 39.📚 Good or bad for training a model: copies of one photo? (a) good for training (b) bad for training
40. 40.True or false: the message “You won a free phone! Click now!” should be labelled “spam”. (a) True (b) False

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