Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 385 · 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 is the odd one out? (a) photos in many lights (b) wrong labels (c) checking labels twice (d) examples of every type
2. 2.🧠 Machine learning is a way for computers to… (a) clean screens (b) learn from data (c) charge faster (d) print pages
3. 3.📚 Good or bad for training a model: testing on training data? (a) bad for training (b) good for training
4. 4.🔍 Which is the odd one out? (a) many varied examples (b) wrong labels (c) only one kind of example (d) very few examples
5. 5.Which of these is bad for training a model? (a) correct labels (b) examples of every type (c) clear, sharp examples (d) copies of one photo
6. 6.📚 Good or bad for training a model: labels added at random? (a) bad for training (b) good for training
7. 7.🏷️ 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
8. 8.True or false: “blurry, unclear photos” is good for training a model. (a) False (b) True
9. 9.📚 Good or bad for training a model: copies of one photo? (a) good for training (b) bad for training
10. 10.📚 Good or bad for training a model: only one kind of example? (a) good for training (b) bad for training
11. 11.📚 Good or bad for training a model: examples of every type? (a) bad for training (b) good for training
12. 12.Which of these is good for training a model? (a) many varied examples (b) very few examples (c) blurry, unclear photos (d) only one kind of example
13. 13.📚 Good or bad for training a model: photos in many lights? (a) good for training (b) bad for training
14. 14.Which of these is bad for training a model? (a) examples of every type (b) labels added at random (c) correct labels (d) checking labels twice
15. 15.True or false: “very few examples” is good for training a model. (a) True (b) False
16. 16.Which of these is good for training a model? (a) testing on training data (b) very few examples (c) wrong labels (d) new data for testing
17. 17.📚 Usually, more good examples make a model… (a) change colour (b) forget everything (c) better at its task (d) slower to switch on
18. 18.True or false: the message “Send your password to claim a prize” should be labelled “spam”. (a) True (b) False
19. 19.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it may get it wrong (b) it will shut down (c) it will turn yellow (d) it will be perfect
20. 20.Which of these is bad for training a model? (a) correct labels (b) clear, sharp examples (c) only one kind of example (d) many varied examples
21. 21.🔍 Which is the odd one out? (a) many varied examples (b) checking labels twice (c) copies of one photo (d) new data for testing
22. 22.True or false: the message “Share your OTP to get cashback” should be labelled “not spam”. (a) False (b) True
23. 23.🔍 Which is the odd one out? (a) new data for testing (b) only one kind of example (c) wrong labels (d) blurry, unclear photos
24. 24.Which of these is good for training a model? (a) blurry, unclear photos (b) copies of one photo (c) clear, sharp examples (d) wrong labels
25. 25.🔍 Which is the odd one out? (a) wrong labels (b) very few examples (c) only one kind of example (d) checking labels twice
26. 26.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “spam”. (a) False (b) True
27. 27.True or false: “new data for testing” is bad for training a model. (a) False (b) True
28. 28.True or false: the message “Send your password to claim a prize” should be labelled “not spam”. (a) True (b) False
29. 29.True or false: the message “Your library book is due on Monday” should be labelled “not spam”. (a) False (b) True
30. 30.True or false: “photos in many lights” is good for training a model. (a) True (b) False
31. 31.True or false: the message “Match practice moved to 5 pm” should be labelled “spam”. (a) False (b) True
32. 32.🏷️ What is a “label” in machine learning? (a) a sticker on a laptop (b) the right answer tag (c) the price (d) the font size
33. 33.True or false: “clear, sharp examples” is bad for training a model. (a) True (b) False
34. 34.True or false: the message “Happy birthday! See you at lunch” should be labelled “not spam”. (a) False (b) True
35. 35.True or false: the message “Last chance! Free gift card inside” should be labelled “not spam”. (a) False (b) True
36. 36.🏷️ 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
37. 37.Which of these is bad for training a model? (a) new data for testing (b) blurry, unclear photos (c) photos in many lights (d) many varied examples
38. 38.True or false: “examples of every type” is good for training a model. (a) False (b) True
39. 39.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “The class picnic is on Friday at 8 am” (a) spam (b) not spam
40. 40.True or false: the message “You won a free phone! Click now!” should be labelled “spam”. (a) False (b) True

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