Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 501 · 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: labels added at random? (a) good for training (b) bad for training
2. 2.🧠 Machine learning is a way for computers to… (a) clean screens (b) charge faster (c) learn from data (d) print pages
3. 3.🔍 Which is the odd one out? (a) blurry, unclear photos (b) copies of one photo (c) wrong labels (d) checking labels twice
4. 4.🔍 Which is the odd one out? (a) wrong labels (b) checking labels twice (c) photos in many lights (d) many varied examples
5. 5.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Match practice moved to 5 pm” (a) spam (b) not spam
6. 6.🏷️ 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
7. 7.True or false: the message “Your library book is due on Monday” should be labelled “not spam”. (a) False (b) True
8. 8.True or false: the message “Share your OTP to get cashback” should be labelled “not spam”. (a) False (b) True
9. 9.True or false: “blurry, unclear photos” is bad for training a model. (a) False (b) True
10. 10.🔍 Which is the odd one out? (a) clear, sharp examples (b) only one kind of example (c) many varied examples (d) correct labels
11. 11.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it may get it wrong (b) it will be perfect (c) it will turn yellow (d) it will shut down
12. 12.🏷️ 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
13. 13.🔍 Which is the odd one out? (a) testing on training data (b) only one kind of example (c) copies of one photo (d) many varied examples
14. 14.Which of these is good for training a model? (a) blurry, unclear photos (b) testing on training data (c) copies of one photo (d) new data for testing
15. 15.🐶 To teach a model to spot dogs in photos, what do you give it? (a) a list of rules only (b) many labelled photos (c) one single photo (d) a song about dogs
16. 16.📚 Good or bad for training a model: wrong labels? (a) good for training (b) bad for training
17. 17.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “not spam”. (a) True (b) False
18. 18.📚 Usually, more good examples make a model… (a) forget everything (b) better at its task (c) change colour (d) slower to switch on
19. 19.True or false: “copies of one photo” is bad for training a model. (a) True (b) False
20. 20.🔍 Which is the odd one out? (a) correct labels (b) many varied examples (c) clear, sharp examples (d) blurry, unclear photos
21. 21.🔍 Which is the odd one out? (a) blurry, unclear photos (b) copies of one photo (c) only one kind of example (d) photos in many lights
22. 22.True or false: “clear, sharp examples” is good for training a model. (a) False (b) True
23. 23.🔍 Which is the odd one out? (a) clear, sharp examples (b) testing on training data (c) examples of every type (d) checking labels twice
24. 24.True or false: “new data for testing” is bad for training a model. (a) False (b) True
25. 25.🔍 Which is the odd one out? (a) correct labels (b) clear, sharp examples (c) checking labels twice (d) very few examples
26. 26.📚 Good or bad for training a model: checking labels twice? (a) good for training (b) bad for training
27. 27.📚 Good or bad for training a model: examples of every type? (a) bad for training (b) good for training
28. 28.🏷️ What is a “label” in machine learning? (a) the font size (b) the right answer tag (c) the price (d) a sticker on a laptop
29. 29.True or false: “very few examples” is bad for training a model. (a) True (b) False
30. 30.Which of these is good for training a model? (a) testing on training data (b) blurry, unclear photos (c) clear, sharp examples (d) very few examples
31. 31.True or false: the message “Science project groups are on the board” should be labelled “spam”. (a) False (b) True
32. 32.True or false: the message “Science project groups are on the board” should be labelled “not spam”. (a) True (b) False
33. 33.Which of these is bad for training a model? (a) clear, sharp examples (b) checking labels twice (c) testing on training data (d) new data for testing
34. 34.Which of these is bad for training a model? (a) correct labels (b) new data for testing (c) wrong labels (d) clear, sharp examples
35. 35.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “spam”. (a) True (b) False
36. 36.True or false: “correct labels” is good for training a model. (a) False (b) True
37. 37.📚 Good or bad for training a model: many varied examples? (a) bad for training (b) good for training
38. 38.🏷️ 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
39. 39.True or false: “blurry, unclear photos” is good for training a model. (a) True (b) False
40. 40.True or false: the message “Last chance! Free gift card inside” should be labelled “spam”. (a) False (b) True

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