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description of imdb dataset python

embedding_vector_length = 32
model = Sequential()
model.add(Embedding(max_words, embedding_vector_length, input_length=max_review_length))
model.add(LSTM(100))
model.add(Dense(1, activation='sigmoid'))
model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])
print(model.summary())
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