神经网络python库keras在windows下部署过程，带下载链接

pip install tensorflow

from keras.models import Sequential
from keras.layers import Dense, Activation
model.add(Dense(units=25, input_dim=64))
model=Sequential()   #网络基本结构
model.add(Dense(units=25, input_dim=8*8))  #添加一个隐层，有25个节点，64个输入
model.add(Activation("sigmoid"))  #设置激活函数logistic
model.add(Dense(units=10))  #增加一个输出层
model.add(Activation('sigmoid'))  # 设置激活函数

data=open('orc-data.csv','r').readlines()
data=[line.strip().split(',') for line in data]
data=[list(map(row, int)) for row in data]
data=[list(map(int, row)) for row in data]
X=[row[1:] for row in data]
temp_Y=[row[0] for row in data]
Y=[]
for y in temp_Y:
	v=[0]*10
	v[y]=1
	Y.append(v)

model.compile(loss='categorical_crossentropy',
				optimizer='adam',
				metrics=['accuracy'])
model.fid(X, Y, batch_size=100, nb_epoch=20)