microsoft/AI-For-Beginners
Publicmirrored fromhttps://github.com/microsoft/AI-For-BeginnersAvailable
etc/quiz-app/src/assets/translations/en/lesson-12.json
123lines · modecode
| 1 | [ |
| 2 | { |
| 3 | "title": "AI for Beginners: Quizzes", |
| 4 | "complete": "Congratulations, you completed the quiz!", |
| 5 | "error": "Sorry, try again", |
| 6 | "quizzes": [ |
| 7 | { |
| 8 | "id": 112, |
| 9 | "title": "Segmentation: Pre Quiz", |
| 10 | "quiz": [ |
| 11 | { |
| 12 | "questionText": "There are ____ segmentation algorithms?", |
| 13 | "answerOptions": [ |
| 14 | { |
| 15 | "answerText": "1", |
| 16 | "isCorrect": false |
| 17 | }, |
| 18 | { |
| 19 | "answerText": "2", |
| 20 | "isCorrect": true |
| 21 | }, |
| 22 | { |
| 23 | "answerText": "3", |
| 24 | "isCorrect": false |
| 25 | } |
| 26 | ] |
| 27 | }, |
| 28 | { |
| 29 | "questionText": "Segmentation is a _____ task", |
| 30 | "answerOptions": [ |
| 31 | { |
| 32 | "answerText": "computer vision", |
| 33 | "isCorrect": true |
| 34 | }, |
| 35 | { |
| 36 | "answerText": "natural language processing", |
| 37 | "isCorrect": false |
| 38 | }, |
| 39 | { |
| 40 | "answerText": "neural networks", |
| 41 | "isCorrect": false |
| 42 | } |
| 43 | ] |
| 44 | }, |
| 45 | { |
| 46 | "questionText": "Segmentation networks consist of ____ and ____ parts", |
| 47 | "answerOptions": [ |
| 48 | { |
| 49 | "answerText": "classifier, divider", |
| 50 | "isCorrect": false |
| 51 | }, |
| 52 | { |
| 53 | "answerText": "encoder, decoder", |
| 54 | "isCorrect": true |
| 55 | }, |
| 56 | { |
| 57 | "answerText": "generator, discriminator", |
| 58 | "isCorrect": false |
| 59 | } |
| 60 | ] |
| 61 | } |
| 62 | ] |
| 63 | }, |
| 64 | { |
| 65 | "id": 212, |
| 66 | "title": "Segmentation: Post Quiz", |
| 67 | "quiz": [ |
| 68 | { |
| 69 | "questionText": "____ extracts features from input image", |
| 70 | "answerOptions": [ |
| 71 | { |
| 72 | "answerText": "decoder", |
| 73 | "isCorrect": false |
| 74 | }, |
| 75 | { |
| 76 | "answerText": "generator", |
| 77 | "isCorrect": false |
| 78 | }, |
| 79 | { |
| 80 | "answerText": "encoder", |
| 81 | "isCorrect": true |
| 82 | } |
| 83 | ] |
| 84 | }, |
| 85 | { |
| 86 | "questionText": "____ transforms input features into mask image", |
| 87 | "answerOptions": [ |
| 88 | { |
| 89 | "answerText": "decoder", |
| 90 | "isCorrect": true |
| 91 | }, |
| 92 | { |
| 93 | "answerText": "generator", |
| 94 | "isCorrect": false |
| 95 | }, |
| 96 | { |
| 97 | "answerText": "encoder", |
| 98 | "isCorrect": false |
| 99 | } |
| 100 | ] |
| 101 | }, |
| 102 | { |
| 103 | "questionText": "SegNet relies on ____ to train multi-layered network", |
| 104 | "answerOptions": [ |
| 105 | { |
| 106 | "answerText": "batch normalization", |
| 107 | "isCorrect": true |
| 108 | }, |
| 109 | { |
| 110 | "answerText": "height normalization", |
| 111 | "isCorrect": false |
| 112 | }, |
| 113 | { |
| 114 | "answerText": "weight normalization", |
| 115 | "isCorrect": false |
| 116 | } |
| 117 | ] |
| 118 | } |
| 119 | ] |
| 120 | } |
| 121 | ] |
| 122 | } |
| 123 | ] |