Machine Learning for Kids Worksheet

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

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