1、程式碼

import tensorflow as tf
import numpy as np

# 使用 NumPy 生成假資料(phony data), 總共 100 個點.
x_data = np.float32(np.random.rand(2, 100)) # 隨機輸入
y_data = np.dot([0.100, 0.200], x_data) + 0.300

# 構造一個線性模型
# 
b = tf.Variable(tf.zeros([1]))
W = tf.Variable(tf.random_uniform([1, 2], -1.0, 1.0))
y = tf.matmul(W, x_data) + b

# 最小化方差
loss = tf.reduce_mean(tf.square(y - y_data))
optimizer = tf.train.GradientDescentOptimizer(0.5)
train = optimizer.minimize(loss)

# 初始化變數
init = tf.global_variables_initializer()

# 啟動圖 (graph)
sess = tf.Session()
sess.run(init)

# 擬合平面
for step in range(0, 201):
    sess.run(train)
    if step % 20 == 0:
        print(step, sess.run(W), sess.run(b))