Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 533 · 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.📚 Good or bad for training a model: blurry, unclear photos? (a) bad for training (b) good for training
2. 2.True or false: “many varied examples” is bad for training a model. (a) True (b) False
3. 3.🔍 Which is the odd one out? (a) only one kind of example (b) labels added at random (c) wrong labels (d) photos in many lights
4. 4.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your library book is due on Monday” (a) spam (b) not spam
5. 5.🏷️ 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
6. 6.Which of these is good for training a model? (a) labels added at random (b) testing on training data (c) photos in many lights (d) blurry, unclear photos
7. 7.📚 Good or bad for training a model: copies of one photo? (a) bad for training (b) good for training
8. 8.🔍 Which is the odd one out? (a) correct labels (b) very few examples (c) checking labels twice (d) clear, sharp examples
9. 9.🏷️ 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
10. 10.📚 Usually, more good examples make a model… (a) change colour (b) forget everything (c) slower to switch on (d) better at its task
11. 11.📚 Good or bad for training a model: many varied examples? (a) bad for training (b) good for training
12. 12.📚 Good or bad for training a model: very few examples? (a) good for training (b) bad for training
13. 13.🐶 To teach a model to spot dogs in photos, what do you give it? (a) a song about dogs (b) many labelled photos (c) a list of rules only (d) one single photo
14. 14.🏷️ 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
15. 15.True or false: “checking labels twice” is bad for training a model. (a) False (b) True
16. 16.🔍 Which is the odd one out? (a) copies of one photo (b) wrong labels (c) clear, sharp examples (d) testing on training data
17. 17.🧠 Machine learning is a way for computers to… (a) charge faster (b) clean screens (c) print pages (d) learn from data
18. 18.🏷️ 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
19. 19.True or false: the message “Send your password to claim a prize” should be labelled “not spam”. (a) False (b) True
20. 20.📚 Good or bad for training a model: new data for testing? (a) bad for training (b) good for training
21. 21.True or false: the message “Match practice moved to 5 pm” should be labelled “not spam”. (a) True (b) False
22. 22.True or false: “very few examples” is good for training a model. (a) False (b) True
23. 23.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “not spam”. (a) False (b) True
24. 24.🔍 Which is the odd one out? (a) many varied examples (b) copies of one photo (c) blurry, unclear photos (d) testing on training data
25. 25.🔍 Which is the odd one out? (a) clear, sharp examples (b) correct labels (c) checking labels twice (d) only one kind of example
26. 26.Which of these is bad for training a model? (a) testing on training data (b) clear, sharp examples (c) photos in many lights (d) new data for testing
27. 27.Which of these is bad for training a model? (a) examples of every type (b) correct labels (c) very few examples (d) checking labels twice
28. 28.Which of these is good for training a model? (a) only one kind of example (b) very few examples (c) new data for testing (d) copies of one photo
29. 29.🔍 Which is the odd one out? (a) testing on training data (b) new data for testing (c) correct labels (d) examples of every type
30. 30.True or false: “checking labels twice” is good for training a model. (a) True (b) False
31. 31.True or false: the message “Your library book is due on Monday” should be labelled “spam”. (a) True (b) False
32. 32.True or false: “blurry, unclear photos” is good for training a model. (a) False (b) True
33. 33.🔍 Which is the odd one out? (a) labels added at random (b) wrong labels (c) new data for testing (d) blurry, unclear photos
34. 34.📚 Good or bad for training a model: labels added at random? (a) good for training (b) bad for training
35. 35.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “spam”. (a) True (b) False
36. 36.True or false: “only one kind of example” is bad for training a model. (a) False (b) True
37. 37.📚 Good or bad for training a model: checking labels twice? (a) good for training (b) bad for training
38. 38.True or false: “copies of one photo” is bad for training a model. (a) False (b) True
39. 39.📚 Good or bad for training a model: correct labels? (a) bad for training (b) good for training
40. 40.True or false: “many varied examples” is good for training a model. (a) True (b) False

Free ai for students lessons, practice and worksheets at talentjr.in/ai-for-students