功能：拟合y=0.1x+0.3，python代码
#encoding=utf-8
import tensorflow as tf
import numpy as np
#creat data
#创建100个随机数，及真实输出
x_data = np.random.rand(100).astype(np.float32)
y_data = x_data*0.1+0.3
#create tensorflow structure start#
#定义权重（1维，-1~1之间）和偏置(1维，0)
Weights = tf.Variable(tf.random_uniform([1],-1.0,1.0))
biases = tf.Variable(tf.zeros([1]))
#求预测值
y = Weights*x_data + biases
#定义损失函数(平方根)
loss = tf.reduce_mean(tf.square(y-y_data))
#最优化算法
optimizer = tf.train.GradientDescentOptimizer(0.5)
#训练变量train
train = optimizer.minimize(loss)
#初始化变量init
init = tf.initialize_all_variables()
#create tensorflow structure end#
#创建会话
sess = tf.Session()
#会话初始化
sess.run(init)
#训练201步
for step in range(201):
#执行一次训练
sess.run(train)
if step % 20 == 0:
print step,sess.run(Weights),sess.run(biases)#输出参数查看效果
