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shgidi/1_layer_nn.py

Created May 23, 2017 14:07
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1_layer_nn.py
#simple model
model = Sequential([
#Embedding(vocab_size, vec_size, input_length=seq_len,weights=[emb]),
#Flatten(),
Dense(100, input_dim=test_data.shape[1], init='uniform', activation='relu'),
#Dropout(0.7),
Dense(1, activation='sigmoid')])
model.compile(loss='binary_crossentropy', optimizer=Adam(), metrics=['accuracy'])
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