标签：.sh class target 翻译 for import active data 实现
Tensorflow是目前非常流行的deeplearning框架，学习Tensorflow最好的方法是github上的tf项目https://github.com/tensorflow/tensorflow
或者阅读极客学院主导翻译的中文教程http://wiki.jikexueyuan.com/project/tensorflow-zh/how_tos/reading_data.html 。
此处对tensorflow的基本语法不予赘述，直接贴上源码：
import numpy as np import tensorflow as tf
#准备数据 trainX = np.linspace(-1, 1, 101) trainY = 2 * trainX + np.random.randn(*trainX.shape) * 0.33
#定义模型
def model(X, w): return tf.mul(X, w)
#初始化数据流图 X = tf.placeholder(‘float‘) Y = tf.placeholder(‘float‘) w = tf.Variable(0.0, name = ‘weights‘) y_ = model(X, w)
#评估模型 cost = tf.square(Y - y_) train_op = tf.train.GradientDescentOptimizer(0.01).minimize(cost) sess = tf.InteractiveSession() init = tf.initialize_all_variables() #训练 sess.run(init) for i in range(100): for (x, y) in zip(trainX, trainY): sess.run(train_op, feed_dict = {X: x, Y: y}) print sess.run(w) sess.close()
由浅入深之Tensorflow(1)----linear_regression实现
标签：.sh class target 翻译 for import active data 实现
原文地址：http://www.cnblogs.com/upright/p/6136193.html
