TensorFlow机器学习小案例（三）

利用TensorFlow实现线性回归模型demo

import numpy as np
import tensorflow as tf
import matplotlib.pyplot as plt

# 随机生成1000个点，围绕在y=0.1x+0.3的直线周围
num_points = 1000
vectors_set = []
for i in range(num_points):
          x1 = np.random.normal(0.0,0.55)
          y1 = x1 * 0.1 + 0.3 + np.random.normal(0.0,0.03)
          vectors_set.append([x1, y1])

# 生成一些样本
x_data = [v[0] for v in vectors_set]
y_data = [v[1] for v in vectors_set]

plt.scatter(x_data, y_data, c='r', label='Original data')
#plt.plot(x_data, y_data, c='r', label='Original data') 画线
plt.legend()
plt.show()