# Create first network with Keras
from keras.models import Sequential
from keras.layers import Dense
import numpy as np
# fix random seed for reproducibility
seed = 7
X = np.random.rand(600,8)
Y = np.zeros(600)
select = np.random.randint(0,600,100)
Y[select]=1

model = Sequential()
model.add(Dense(12, input_dim=8, init='uniform', activation='relu'))
model.add(Dense(8, init='uniform', activation='relu'))
model.add(Dense(1, init='uniform', activation='sigmoid'))
# Compile model
model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])
# Fit the model
model.fit(X, Y, nb_epoch=5, batch_size=10,  verbose=2)