Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 207 · 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.🏷️ What is a “label” in machine learning? (a) a sticker on a laptop (b) the price (c) the font size (d) the right answer tag
2. 2.🏷️ 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
3. 3.True or false: “clear, sharp examples” is good for training a model. (a) True (b) False
4. 4.📚 Good or bad for training a model: new data for testing? (a) good for training (b) bad for training
5. 5.📚 Good or bad for training a model: copies of one photo? (a) good for training (b) bad for training
6. 6.🔍 Which is the odd one out? (a) copies of one photo (b) wrong labels (c) new data for testing (d) testing on training data
7. 7.🔍 Which is the odd one out? (a) examples of every type (b) photos in many lights (c) wrong labels (d) correct labels
8. 8.Which of these is bad for training a model? (a) only one kind of example (b) new data for testing (c) examples of every type (d) correct labels
9. 9.True or false: “labels added at random” is good for training a model. (a) True (b) False
10. 10.📚 Good or bad for training a model: photos in many lights? (a) good for training (b) bad for training
11. 11.Which of these is bad for training a model? (a) new data for testing (b) correct labels (c) photos in many lights (d) testing on training data
12. 12.📚 Good or bad for training a model: only one kind of example? (a) good for training (b) bad for training
13. 13.True or false: the message “Last chance! Free gift card inside” should be labelled “spam”. (a) False (b) True
14. 14.True or false: “only one kind of example” is good for training a model. (a) True (b) False
15. 15.🔍 Which is the odd one out? (a) clear, sharp examples (b) photos in many lights (c) checking labels twice (d) blurry, unclear photos
16. 16.🏷️ 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
17. 17.True or false: “many varied examples” is good for training a model. (a) False (b) True
18. 18.🐶 To teach a model to spot dogs in photos, what do you give it? (a) one single photo (b) a list of rules only (c) a song about dogs (d) many labelled photos
19. 19.🔍 Which is the odd one out? (a) photos in many lights (b) testing on training data (c) new data for testing (d) examples of every type
20. 20.True or false: “photos in many lights” is good for training a model. (a) False (b) True
21. 21.True or false: “very few examples” is bad for training a model. (a) True (b) False
22. 22.📚 Good or bad for training a model: labels added at random? (a) bad for training (b) good for training
23. 23.🥭 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 shut down (d) it will turn yellow
24. 24.Which of these is good for training a model? (a) many varied examples (b) very few examples (c) only one kind of example (d) blurry, unclear photos
25. 25.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Happy birthday! See you at lunch” (a) not spam (b) spam
26. 26.Which of these is good for training a model? (a) very few examples (b) examples of every type (c) labels added at random (d) testing on training data
27. 27.Which of these is good for training a model? (a) very few examples (b) new data for testing (c) labels added at random (d) copies of one photo
28. 28.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “not spam”. (a) True (b) False
29. 29.🔍 Which is the odd one out? (a) wrong labels (b) labels added at random (c) many varied examples (d) copies of one photo
30. 30.📚 Good or bad for training a model: examples of every type? (a) bad for training (b) good for training
31. 31.True or false: “testing on training data” is bad for training a model. (a) False (b) True
32. 32.True or false: “examples of every type” is good for training a model. (a) False (b) True
33. 33.True or false: the message “Your library book is due on Monday” should be labelled “not spam”. (a) True (b) False
34. 34.📚 Usually, more good examples make a model… (a) change colour (b) better at its task (c) forget everything (d) slower to switch on
35. 35.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Last chance! Free gift card inside” (a) spam (b) not spam
36. 36.True or false: the message “Last chance! Free gift card inside” should be labelled “not spam”. (a) True (b) False
37. 37.🔍 Which is the odd one out? (a) very few examples (b) checking labels twice (c) new data for testing (d) many varied examples
38. 38.Which of these is bad for training a model? (a) correct labels (b) clear, sharp examples (c) checking labels twice (d) labels added at random
39. 39.🔍 Which is the odd one out? (a) very few examples (b) testing on training data (c) copies of one photo (d) examples of every type
40. 40.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your account is locked, pay ₹99 now” (a) spam (b) not spam

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