freeCodeCamp/curriculum/challenges/chinese/11-machine-learning-with-python/tensorflow/natural-language-processing-with-rnns-building-the-model.md
Oliver Eyton-Williams ee1e8abd87
feat(curriculum): restore seed + solution to Chinese (#40683)
* 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>
2021-01-12 19:31:00 -07:00

965 B

id, challengeType, videoId, dashedName
id challengeType videoId dashedName
5e8f2f13c4cdbe86b5c72da1 11 32WBFS7lfsw natural-language-processing-with-rnns-building-the-model

--question--

--text--

Fill in the blanks below to complete the build_model function:

def build_mode(vocab_size, embedding_dim, rnn_units, batch_size):
    model = tf.keras.Sequential([
        tf.keras.layers.Embedding(vocab_size,
                                  embedding_dim,
                                  batch_input_shape=[batch_size, None]),
        tf.keras.layers.__A__(rnn_units,
                              return_sequences=__B__,
                              recurrent_initializer='glorot_uniform),
        tf.keras.layers.Dense(__C__)
    ])
    __D__

--answers--

A: ELU

B: True

C: vocab_size

D: return model


A: LSTM

B: False

C: batch_size

D: return model


A: LSTM

B: True

C: vocab_size

D: return model

--video-solution--

3