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  1. import numpy as np
  2. from keras.models import Sequential
  3. from keras.layers import Dense
  4.  
  5. # create some dummy data
  6. X = np.random.rand(100, 10)
  7. y = np.random.randint(2, size=100)
  8.  
  9. # define the model
  10. model = Sequential()
  11. model.add(Dense(8, input_dim=10, activation='relu'))
  12. model.add(Dense(1, activation='sigmoid'))
  13.  
  14. # compile the model
  15. model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])
  16.  
  17. # fit the model on the data
  18. model.fit(X, y, epochs=10, batch_size=16)
  19.  
  20. # evaluate the model on new data
  21. X_test = np.random.rand(10, 10)
  22. y_pred = model.predict(X_test)
  23. print(y_pred)
  24.  
Success #stdin #stdout 4.68s 347028KB
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Standard input is empty
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Epoch 1/10

1/7 [===>..........................] - ETA: 2s - loss: 0.5734 - accuracy: 0.6875
7/7 [==============================] - 0s 1ms/step - loss: 0.6845 - accuracy: 0.6300
Epoch 2/10

1/7 [===>..........................] - ETA: 0s - loss: 0.7068 - accuracy: 0.6250
7/7 [==============================] - 0s 2ms/step - loss: 0.6816 - accuracy: 0.6200
Epoch 3/10

1/7 [===>..........................] - ETA: 0s - loss: 0.6421 - accuracy: 0.6250
7/7 [==============================] - 0s 1ms/step - loss: 0.6799 - accuracy: 0.6000
Epoch 4/10

1/7 [===>..........................] - ETA: 0s - loss: 0.5943 - accuracy: 0.7500
7/7 [==============================] - 0s 1ms/step - loss: 0.6781 - accuracy: 0.6000
Epoch 5/10

1/7 [===>..........................] - ETA: 0s - loss: 0.6551 - accuracy: 0.6875
7/7 [==============================] - 0s 1ms/step - loss: 0.6776 - accuracy: 0.6000
Epoch 6/10

1/7 [===>..........................] - ETA: 0s - loss: 0.7433 - accuracy: 0.4375
7/7 [==============================] - 0s 1ms/step - loss: 0.6766 - accuracy: 0.6000
Epoch 7/10

1/7 [===>..........................] - ETA: 0s - loss: 0.7031 - accuracy: 0.4375
7/7 [==============================] - 0s 1ms/step - loss: 0.6755 - accuracy: 0.5900
Epoch 8/10

1/7 [===>..........................] - ETA: 0s - loss: 0.7029 - accuracy: 0.7500
7/7 [==============================] - 0s 1ms/step - loss: 0.6748 - accuracy: 0.5900
Epoch 9/10

1/7 [===>..........................] - ETA: 0s - loss: 0.6941 - accuracy: 0.5625
7/7 [==============================] - 0s 1ms/step - loss: 0.6743 - accuracy: 0.6000
Epoch 10/10

1/7 [===>..........................] - ETA: 0s - loss: 0.6924 - accuracy: 0.5625
7/7 [==============================] - 0s 2ms/step - loss: 0.6734 - accuracy: 0.6100
[[0.45809937]
 [0.6846294 ]
 [0.5104834 ]
 [0.6624383 ]
 [0.63145536]
 [0.5679933 ]
 [0.5651702 ]
 [0.52085674]
 [0.4555182 ]
 [0.54719037]]
https://ideone.com/kyuRnJ
language:
Python 3 (python  3.12)
created:
2 years ago
visibility:
public

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