Wu Enda linear regression of machine learning

It mainly records the process of practicing code after class

The workbench - Heywhale.com

Based on this

One . Simple exercises

Output identity matrix

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt

a = np.eye(5)
print(a)

Two . Drawing of data

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt

path = 'C:/Users/szuacm/Desktop/ machine learning / data /1.txt'
data = pd.read_csv(path, header= 0, names = ['Population', 'Profit'])
print(data)

data.plot(kind='scatter', x='Population', y='Profit', figsize=(12,8))
plt.show()

3、 ... and . Code

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt

def computecost(x, y, theta):
    t = np.power(x * theta.T - y, 2)
    return sum(t) / (2 * len(x))

path =  'in.txt'
data = pd.read_csv(path, header = None, names = ['Population', 'Profit'])

data.insert(0, 'Ones', 1)
cols = data.shape[1]
x = data.iloc[:, 0:cols - 1]
y = data.iloc[:, cols - 1:cols]

x = np.matrix(x.values)
y = np.matrix(y.values)
theta = np.matrix([0, 0])

print(x.shape, theta.shape, y.shape)
print(computecost(x, y, theta))

## Change the data again   The data is wrong