线性模型（刘二大人）

课堂代码：

import  numpy as np
import  matplotlib.pyplot as plt
def forward(x):
    return x*w
def loss(x,y):
    y_pred=forward(x);
    return (y-y_pred)**2
x_data=[1.0,2.0,3.0]
y_data=[2.0,4.0,6.0]
w_list=[]
mse_list=[]
for w in np.arange(0.0,4.1,0.1):
    l_sum=0
    for x_val,y_val in zip(x_data,y_data):
        loss_val=loss(x_val,y_val)
        l_sum+=loss_val
    mse_list.append(l_sum/3)
    w_list.append(w)
plt.plot(w_list,mse_list)
plt.ylabel('loss')
plt.xlabel('w')
plt.show()

课后作业代码：

import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
x_data=[1.0,2.0,3.0]
y_data=[5.0,8.0,11.0]
def forward(x):
    return w*x+b
def loss(x,y):
    y_pred=forward(x)
    return (y-y_pred)**2
W=np.arange(0.0,4.1,0.1)
B=np.arange(0.0,4.1,0.1)
w,b=np.meshgrid(W,B)
l_sum=0
for x_val,y_val in zip(x_data,y_data):
    loss_val=loss(x_val,y_val)
    l_sum+=loss_val
fig=plt.figure()  #创建画板
ax=Axes3D(fig)
ax.plot_surface(w,b,l_sum/3)
plt.show()