Keras: Deep Learning library

1. Sequence classification with 1D convolutions:
   
2. 
   
3. from keras.models import Sequential
   
4. from keras.layers import Dense, Dropout
   
5. from keras.layers import Embedding
   
6. from keras.layers import Conv1D, GlobalAveragePooling1D, MaxPooling1D
   
7. 
   
8. model = Sequential()
   
9. model.add(Conv1D(64, 3, activation='relu', input_shape=(seq_length, 100)))
   
10. model.add(Conv1D(64, 3, activation='relu'))
    
11. model.add(MaxPooling1D(3))
    
12. model.add(Conv1D(128, 3, activation='relu'))
    
13. model.add(Conv1D(128, 3, activation='relu'))
    
14. model.add(GlobalAveragePooling1D())
    
15. model.add(Dropout(0.5))
    
16. model.add(Dense(1, activation='sigmoid'))
    
17. 
    
18. model.compile(loss='binary_crossentropy',
    
19.               optimizer='rmsprop',
    
20.               metrics=['accuracy'])
    
21. 
    
22. model.fit(x_train, y_train, batch_size=16, epochs=10)
    
23. score = model.evaluate(x_test, y_test, batch_size=16)

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