Tensorflow学习一

Tensorflow学习小例子

  import tensorflow as tf
    import numpy as np
    x_data = np.random.rand(100).astype(np.float32)#随机生成的数
    y_data = x_data*0.1+0.3#要学习的模型

    ## create tensorflow structure start###

Weights = tf.Variable(tf.random_uniform([1],-1.0,1.0))#1维，范围-1到1
biases = tf.Variable(tf.zeros([1]))#初始为0

y = Weights*x_data + biases#预测数据
loss = tf.reduce_mean(tf.square(y-y_data))
optimizer = tf.train.GradientDescentOptimizer(0.5)#0.5学习效率
train = optimizer.minimize(loss)

init = tf.initialize_all_variables()#初始化
## create tensorflow structure end ###
sess = tf.Session()
sess.run(init)#激活神经网络
for step in range(201):
    sess.run(train)# 激活train
    if step % 20 ==0:
        print(step,sess.run(Weights),sess.run(biases))