Keras入门简单例子
发布于 2020-03-11 00:01:10
import numpy as np
from keras.models import Sequential
from keras.layers import Dense
data = np.random.random((1000, 1000))
labels = np.random.randint(2, size=(1000, 1))
model = Sequential()
model.add(Dense(32,
activation='relu',
input_dim=100))
model.add(Dense(1, activation='sigmoid'))
model.compile(optimize='rmsprop', loss='binary_crossentropy',
metrics=['accuracy'])
model.fit(data, labels, epochs=10, batch_size=32)
predictions = model.predict(data)0 条评论
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