Machine Learning for Kids Worksheet

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

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