linear_reg1.py

from sklearn.datasets import make_regression
import matplotlib.pyplot as plt
%matplotlib inline

#generating random dataset for linear regression
x,y,coef=make_regression(n_samples=10,n_features=1,n_informative=1,n_targets=1,noise=
                         3,bias=1.0,coef=True,random_state=42)

#modelling
from sklearn.linear_model import LinearRegression

model=LinearRegression(fit_intercept=False)

model.fit(x,y)

y_pred=model.predict(x)

#plot
plt.scatter(y,y_pred)
plt.plot(y,y,color='r')
plt.show ()

Hi, is it possible to execute this code with a sample of data online ?

Hey, just updated the code. Feel free the run in ur notebook.