Explain how to implement Multiple Linear regression in python

First we import all the libraries

import pandas as pd

import numpy as np

import matplotlib.pyplot as plt

import seaborn as sns

USAhousing = pd.read_csv('USA_Housing.csv')

X = USAhousing[['Avg. Area Income', 'Avg. Area House Age', 'Avg. Area Number of Rooms',

               'Avg. Area Number of Bedrooms', 'Area Population']]

y = USAhousing['Price']

Now we split the model

from sklearn.model_selection import train_test_split

X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.4, random_state=101)

Now we fit and predict the model

from sklearn.linear_model import LinearRegression

lm = LinearRegression()

lm.fit(X_train,y_train)

predictions = lm.predict(X_test)