ee1e8abd87
* feat(tools): add seed/solution restore script * chore(curriculum): remove empty sections' markers * chore(curriculum): add seed + solution to Chinese * chore: remove old formatter * fix: update getChallenges parse translated challenges separately, without reference to the source * chore(curriculum): add dashedName to English * chore(curriculum): add dashedName to Chinese * refactor: remove unused challenge property 'name' * fix: relax dashedName requirement * fix: stray tag Remove stray `pre` tag from challenge file. Signed-off-by: nhcarrigan <nhcarrigan@gmail.com> Co-authored-by: nhcarrigan <nhcarrigan@gmail.com>
51 lines
654 B
Markdown
51 lines
654 B
Markdown
---
|
|
id: 5e8f2f13c4cdbe86b5c72d9e
|
|
title: 'Natural Language Processing With RNNs: Sentiment Analysis'
|
|
challengeType: 11
|
|
videoId: lYeLtu8Nq7c
|
|
dashedName: natural-language-processing-with-rnns-sentiment-analysis
|
|
---
|
|
|
|
# --question--
|
|
|
|
## --text--
|
|
|
|
Fill in the blanks below to create the model for the RNN:
|
|
|
|
```py
|
|
model = __A__.keras.Sequential([
|
|
__A__.keras.layers.__B__(88584, 32),
|
|
__A__.keras.layers.__C__(32),
|
|
__A__.keras.layers.DENSE(1, activation='sigmoid')
|
|
])
|
|
```
|
|
|
|
## --answers--
|
|
|
|
A: `tensor_flow`
|
|
|
|
B: `embedding`
|
|
|
|
C: `LSTM`
|
|
|
|
---
|
|
|
|
A: `tf`
|
|
|
|
B: `Embedding`
|
|
|
|
C: `AlphaDropout`
|
|
|
|
---
|
|
|
|
A: `tf`
|
|
|
|
B: `Embedding`
|
|
|
|
C: `LSTM`
|
|
|
|
## --video-solution--
|
|
|
|
3
|
|
|