tensorflow从人们到升仙（1）

tensorflow的hello world

来一段性感的代码：

import tensorflow as tfimport numpy as np#创建数据x = np.random.rand(200).astype(np.float32)y_data = x * 0.1 + 0.3 # y = weights * x + biases#搭建模型weights = tf.Variable(tf.random_uniform([1],-1.0,1.0))biases = tf.Variable(tf.zeros([1]))y = weights * x + biases  #神经网络经典传递#计算误差,均方差公式loss = tf.reduce_mean(tf.square(y - y_data))#误差传递optimizer = tf.train.GradientDescentOptimizer(0.5)train = optimizer.minimize(loss)#训练init = tf.global_variables_initializer()sess = tf.Session()sess.run(init)for step in range(401):    sess.run(train)    if step % 20 == 0:        print(step,sess.run(weights),sess.run(biases))

预测结果：

0 [-0.50229931] [ 0.81214285]20 [-0.05962949] [ 0.38132203]40 [ 0.06281903] [ 0.31894156]60 [ 0.09133982] [ 0.30441189]80 [ 0.09798285] [ 0.30102763]100 [ 0.09953018] [ 0.30023935]120 [ 0.09989057] [ 0.30005577]140 [ 0.09997453] [ 0.30001298]160 [ 0.09999406] [ 0.30000302]180 [ 0.09999864] [ 0.3000007]200 [ 0.09999968] [ 0.30000016]220 [ 0.0999999] [ 0.30000007]240 [ 0.0999999] [ 0.30000007]260 [ 0.0999999] [ 0.30000007]280 [ 0.0999999] [ 0.30000007]300 [ 0.0999999] [ 0.30000007]320 [ 0.0999999] [ 0.30000007]340 [ 0.0999999] [ 0.30000007]360 [ 0.0999999] [ 0.30000007]380 [ 0.0999999] [ 0.30000007]400 [ 0.0999999] [ 0.30000007]