Tensorflow快餐教程(7) - 梯度下降
梯度下降
学习完基础知识和矩阵运算之后,我们再回头看下第一节讲的线性回归的代码:
import tensorflow as tf
import numpy as np
trX = np.linspace(-1, 1, 101)
trY = 2 * trX + np.random.randn(*trX.shape) * 0.33 # 创建一些线性值附近的随机值
X = tf.placeholder("float")
Y = tf.placeholder("float")
def model(X, w):
return tf.multiply(X, w) # X*w线性求值,非常简单
w = tf.Variable(0.0, name="weights")
y_model = model(X, w)
cost = t