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Merge pull request #98 from jlooper/main 

quiz copyediting
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Jen Looper 2022-05-24 10:25:27 -04:00 committed by GitHub
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9 changed files with 24 additions and 24 deletions
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2
etc/quiz-app/src/assets/translations/en/lesson-10.json
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@ -9,7 +9,7 @@
"title": "Generative Adversarial Networks: Pre Quiz",
"quiz": [
{
"questionText": "Gnerators take vectors and produces ____",
"questionText": "Generators take vectors and produce ____",
"answerOptions": [
{
"answerText": "videos",

6
etc/quiz-app/src/assets/translations/en/lesson-16.json
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@ -26,7 +26,7 @@
]
},
{
"questionText": "Simple RNN cell has two weight _____",
"questionText": "A simple RNN cell has two weight _____",
"answerOptions": [
{
"answerText": "matrices",
@ -66,7 +66,7 @@
"title": "RNN: Post Quiz",
"quiz": [
{
"questionText": "_____ takes some information from the input and hidden vector, and inserts it into state",
"questionText": "_____ takes some information from the input and hidden vector, and inserts it into the state",
"answerOptions": [
{
"answerText": "forget gate",
@ -90,7 +90,7 @@
"isCorrect": true
},
{
"answerText": "nort-west direction",
"answerText": "north-west direction",
"isCorrect": false
},
{

4
etc/quiz-app/src/assets/translations/en/lesson-17.json
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@ -39,7 +39,7 @@
]
},
{
"questionText": "RNN generate texts by generating next output character for each input character",
"questionText": "RNN generates texts by generating the next output character for each input character",
"answerOptions": [
{
"answerText": "true",
@ -58,7 +58,7 @@
"title": "Generative networks: Post Quiz",
"quiz": [
{
"questionText": "Output encoder converts hidden state into _____ output",
"questionText": "An output encoder converts hidden state into _____ output",
"answerOptions": [
{
"answerText": "one-hot-encoded",

4
etc/quiz-app/src/assets/translations/en/lesson-18.json
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@ -9,7 +9,7 @@
"title": "Transformers: Pre Quiz",
"quiz": [
{
"questionText": "Attention mechanism provides a means of _____ the imoact of an inout vector on an output prediction of RNN",
"questionText": "Attention mechanism provides a means of _____ the impact of an inout vector on an output prediction of RNN",
"answerOptions": [
{
"answerText": "weighting",
@ -65,7 +65,7 @@
"questionText": "Positional embedding _____ the original token and its position within the sequence",
"answerOptions": [
{
"answerText": "seperates",
"answerText": "separates",
"isCorrect": false
},
{

2
etc/quiz-app/src/assets/translations/en/lesson-23.json
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@ -107,7 +107,7 @@
"isCorrect": false
},
{
"answerText": "both the above",
"answerText": "both of the above",
"isCorrect": true
}
]

2
etc/quiz-app/src/assets/translations/en/lesson-5.json
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@ -92,7 +92,7 @@
]
},
{
"questionText": "Tensorflow is to ____ while PyTorch is to ____",
"questionText": "TensorFlow is to ____ while PyTorch is to ____",
"answerOptions": [
{
"answerText": "Facebook, Google",

2
etc/quiz-app/src/assets/translations/en/lesson-7.json
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@ -37,7 +37,7 @@
"isCorrect": false
},
{
"answerText": "Tensorflow",
"answerText": "TensorFlow",
"isCorrect": true
}
]

2
etc/quiz-app/src/assets/translations/en/lesson-9.json
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@ -92,7 +92,7 @@
]
},
{
"questionText": "Variational auto-encoders loss funnction does not consist of which of these?",
"questionText": "Variational auto-encoders loss function does not consist of which of these?",
"answerOptions": [
{
"answerText": "reconstruction loss",

24
etc/quiz-src/questions-en.txt
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@ -123,7 +123,7 @@ Lesson 5E Frameworks: Post Quiz
* Binary cross-entropy is also called log loss
+ True
- False
* Tensorflow is to ____ while PyTorch is to ____
* TensorFlow is to ____ while PyTorch is to ____
- Facebook, Google
+ Google, Facebook
- Microsoft, Google
@ -162,7 +162,7 @@ Lesson 7B Convolutional Neural Networks: Pre Quiz
* One of these is not a CNN Architecture
- ResNet
- MobileNet
+ Tensorflow
+ TensorFlow
* CNN are mostly used for computer vision tasks.
+ true
- false
@ -226,13 +226,13 @@ Lesson 9E Autoencoders: Post Quiz
* Auto encoders can be used to effectively remove noise from images
+ true
- false
* Variational auto-encoders loss funnction does not consist of which of these?
* Variational auto-encoders loss function does not consist of which of these?
- reconstruction loss
- KL loss
+ TF loss
Lesson 10B Generative Adversarial Networks: Pre Quiz
* Gnerators take vectors and produces ____
* Generators take vectors and produce ____
- videos
+ image
- gif
@ -342,7 +342,7 @@ Lesson 16B RNN: Pre Quiz
- regression neural network
+ recurrent neural network
- re-iterative neural network
* Simple RNN cell has two weight _____
* A simple RNN cell has two weight _____
+ matrices
- cell
- neuron
@ -352,13 +352,13 @@ Lesson 16B RNN: Pre Quiz
- KNN
Lesson 16E RNN: Post Quiz
* _____ takes some information from the input and hidden vector, and inserts it into state
* _____ takes some information from the input and hidden vector, and inserts it into the state
- forget gate
- output gate
+ input gate
* Bidirectional RNNs runs recurrent computation in _____
+ both directions
- nort-west direction
- north-west direction
- left-right direction
* All RNN Cells have the same shareable weights
+ True
@ -372,12 +372,12 @@ Lesson 17B Generative networks: Pre Quiz
+ one-to-one
- sequence-to-sequence
- one-to-many
* RNN generate texts by generating next output character for each input character
* RNN generates texts by generating the next output character for each input character
+ true
- false
Lesson 17E Generative networks: Post Quiz
* Output encoder converts hidden state into _____ output
* An output encoder converts hidden state into _____ output
+ one-hot-encoded
- sequence
- number
@ -391,7 +391,7 @@ Lesson 17E Generative networks: Post Quiz
- one-to-many
Lesson 18B Transformers: Pre Quiz
* Attention mechanism provides a means of _____ the imoact of an inout vector on an output prediction of RNN
* Attention mechanism provides a means of _____ the impact of an inout vector on an output prediction of RNN
+ weighting
- training
- testing
@ -405,7 +405,7 @@ Lesson 18B Transformers: Pre Quiz
Lesson 18E Transformers: Post Quiz
* Positional embedding _____ the original token and its position within the sequence
- seperates
- separates
- compares
+ embeds
* Multi-Head Attention is used in transformers to give network the power to capture _____ of dependencies
@ -468,4 +468,4 @@ Lesson 23E Multi-Agent Modeling: Post Quiz
* Multi-agent systems are used in:
- video production and systems modeling
- games and automations
+ both the above
+ both of the above