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chore(i18n,learn): processed translations (#44797)

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camperbot
2022-01-17 01:00:34 +05:30
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parent 7968e6d7ec
commit fd9c68ceef
5 changed files with 5 additions and 5 deletions
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2
curriculum/challenges/chinese-traditional/11-machine-learning-with-python/tensorflow/natural-language-processing-with-rnns-sentimental-analysis.md
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@ -20,7 +20,7 @@ dashedName: natural-language-processing-with-rnns-sentiment-analysis
model = __A__.keras.Sequential([ model = __A__.keras.Sequential([
__A__.keras.layers.__B__(88584, 32), __A__.keras.layers.__B__(88584, 32),
__A__.keras.layers.__C__(32), __A__.keras.layers.__C__(32),
__A__.keras.layers.DENSE(1, activation='sigmoid') __A__.keras.layers.Dense(1, activation='sigmoid')
]) ])
``` ```

2
curriculum/challenges/chinese/11-machine-learning-with-python/tensorflow/natural-language-processing-with-rnns-sentimental-analysis.md
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@ -20,7 +20,7 @@ dashedName: natural-language-processing-with-rnns-sentiment-analysis
model = __A__.keras.Sequential([ model = __A__.keras.Sequential([
__A__.keras.layers.__B__(88584, 32), __A__.keras.layers.__B__(88584, 32),
__A__.keras.layers.__C__(32), __A__.keras.layers.__C__(32),
__A__.keras.layers.DENSE(1, activation='sigmoid') __A__.keras.layers.Dense(1, activation='sigmoid')
]) ])
``` ```

2
curriculum/challenges/italian/11-machine-learning-with-python/tensorflow/natural-language-processing-with-rnns-sentimental-analysis.md
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@ -20,7 +20,7 @@ Compila gli spazi vuoti qui sotto per creare il modello per la RNN:
model = __A__.keras.Sequential([ model = __A__.keras.Sequential([
__A__.keras.layers.__B__(88584, 32), __A__.keras.layers.__B__(88584, 32),
__A__.keras.layers.__C__(32), __A__.keras.layers.__C__(32),
__A__.keras.layers.DENSE(1, activation='sigmoid') __A__.keras.layers.Dense(1, activation='sigmoid')
]) ])
``` ```

2
curriculum/challenges/portuguese/11-machine-learning-with-python/tensorflow/natural-language-processing-with-rnns-sentimental-analysis.md
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@ -20,7 +20,7 @@ Preencha as lacunas abaixo para criar o modelo para a RNN:
model = __A__.keras.Sequential([ model = __A__.keras.Sequential([
__A__.keras.layers.__B__(88584, 32), __A__.keras.layers.__B__(88584, 32),
__A__.keras.layers.__C__(32), __A__.keras.layers.__C__(32),
__A__.keras.layers.DENSE(1, activation='sigmoid') __A__.keras.layers.Dense(1, activation='sigmoid')
]) ])
``` ```

2
curriculum/challenges/ukrainian/11-machine-learning-with-python/tensorflow/natural-language-processing-with-rnns-sentimental-analysis.md
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@ -20,7 +20,7 @@ dashedName: natural-language-processing-with-rnns-sentiment-analysis
model = __A__.keras.Sequential([ model = __A__.keras.Sequential([
__A__.keras.layers.__B__(88584, 32), __A__.keras.layers.__B__(88584, 32),
__A__.keras.layers.__C__(32), __A__.keras.layers.__C__(32),
__A__.keras.layers.DENSE(1, activation='sigmoid') __A__.keras.layers.Dense(1, activation='sigmoid')
]) ])
``` ```