from numpy import loadtxt
from sklearn.linear_model import LinearRegression
  
  
x = loadtxt('boston_houses.csv', delimiter=',', skiprows=1)
  
r = LinearRegression().fit(x[:, 1 :], x[:, 0])
  
print(r.intercept_, *r.coef_)
    
и
  
from numpy import loadtxt
import statsmodels.api as sm
  
    
x = loadtxt('boston_houses.csv', delimiter=',', skiprows=1)
  
y = x[:, 0]
x = x[:, 1 :]
x = sm.add_constant(x)
model = sm.OLS(y, x)
   
print(*model.fit().params)

   
from numpy import array, linalg, loadtxt 
  
  
x = loadtxt('boston_houses.csv', delimiter=',', skiprows=1)
  
y = array(x[:, 0])
x[:, 0] = [1.] * len(x)
t = x.T
  
print(*linalg.inv(t.dot(x)).dot(t).dot(y))