Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 454 · 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.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “not spam”. (a) False (b) True
2. 2.True or false: the message “Match practice moved to 5 pm” should be labelled “not spam”. (a) True (b) False
3. 3.Which of these is good for training a model? (a) labels added at random (b) very few examples (c) only one kind of example (d) correct labels
4. 4.🔍 Which is the odd one out? (a) wrong labels (b) very few examples (c) only one kind of example (d) examples of every type
5. 5.Which of these is bad for training a model? (a) very few examples (b) many varied examples (c) examples of every type (d) checking labels twice
6. 6.📚 Good or bad for training a model: clear, sharp examples? (a) good for training (b) bad for training
7. 7.True or false: “labels added at random” is bad for training a model. (a) True (b) False
8. 8.🔍 Which is the odd one out? (a) only one kind of example (b) very few examples (c) wrong labels (d) photos in many lights
9. 9.True or false: the message “You won a free phone! Click now!” should be labelled “spam”. (a) True (b) False
10. 10.📚 Good or bad for training a model: very few examples? (a) bad for training (b) good for training
11. 11.🏷️ What is a “label” in machine learning? (a) the font size (b) the right answer tag (c) a sticker on a laptop (d) the price
12. 12.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “spam”. (a) True (b) False
13. 13.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Please buy milk on the way home” (a) spam (b) not spam
14. 14.Which of these is bad for training a model? (a) many varied examples (b) clear, sharp examples (c) wrong labels (d) correct labels
15. 15.📚 Usually, more good examples make a model… (a) change colour (b) slower to switch on (c) forget everything (d) better at its task
16. 16.True or false: the message “You won a free phone! Click now!” should be labelled “not spam”. (a) True (b) False
17. 17.True or false: “clear, sharp examples” is bad for training a model. (a) True (b) False
18. 18.📚 Good or bad for training a model: new data for testing? (a) good for training (b) bad for training
19. 19.Which of these is bad for training a model? (a) examples of every type (b) many varied examples (c) photos in many lights (d) only one kind of example
20. 20.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will turn yellow (b) it will shut down (c) it may get it wrong (d) it will be perfect
21. 21.📚 Good or bad for training a model: photos in many lights? (a) good for training (b) bad for training
22. 22.🔍 Which is the odd one out? (a) many varied examples (b) testing on training data (c) clear, sharp examples (d) examples of every type
23. 23.True or false: “wrong labels” is bad for training a model. (a) True (b) False
24. 24.True or false: “many varied examples” is good for training a model. (a) True (b) False
25. 25.🏷️ 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
26. 26.🏷️ 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
27. 27.🏷️ 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) not spam (b) spam
28. 28.Which of these is good for training a model? (a) blurry, unclear photos (b) new data for testing (c) testing on training data (d) very few examples
29. 29.Which of these is good for training a model? (a) testing on training data (b) very few examples (c) wrong labels (d) photos in many lights
30. 30.🔍 Which is the odd one out? (a) very few examples (b) blurry, unclear photos (c) copies of one photo (d) new data for testing
31. 31.True or false: “examples of every type” is good for training a model. (a) True (b) False
32. 32.True or false: the message “Send your password to claim a prize” should be labelled “not spam”. (a) True (b) False
33. 33.True or false: the message “Last chance! Free gift card inside” should be labelled “spam”. (a) True (b) False
34. 34.📚 Good or bad for training a model: checking labels twice? (a) bad for training (b) good for training
35. 35.True or false: “new data for testing” is good for training a model. (a) False (b) True
36. 36.True or false: the message “Your library book is due on Monday” should be labelled “not spam”. (a) False (b) True
37. 37.📚 Good or bad for training a model: examples of every type? (a) bad for training (b) good for training
38. 38.🐶 To teach a model to spot dogs in photos, what do you give it? (a) one single photo (b) a song about dogs (c) many labelled photos (d) a list of rules only
39. 39.🔍 Which is the odd one out? (a) correct labels (b) examples of every type (c) many varied examples (d) only one kind of example
40. 40.🔍 Which is the odd one out? (a) clear, sharp examples (b) examples of every type (c) blurry, unclear photos (d) photos in many lights

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