
Coding Demo
Step 1 - Go to https://jupyter.org/try
Before starting code, download the file first.
Step 2 - Click on Try Classic Notebook

Step 3 - Go to file open.

Step 4 - Upload the downloaded file.
Step 5 - Go to your Jupiter Notebook and click on + button as displayed below. At the end new cell will be added.

Step 6 - Copy the code below and paste in the cell.
# import libraries
import numpy as np
import pandas as pd
from sklearn.linear_model import LinearRegression
from sklearn import metrics
# Read the dataset from csv file
df1 = pd.read_csv('ds.csv')
df1.head()
Step 7 - Click on Run Button and you will see the data.

Step 8 - Click on + sign to create new cell and paste the below code.
# Features
X = df1.drop(['MEDV', 'ID'], axis = 1)
# Target
y = df1['MEDV']
# Create a model
lr = LinearRegression()
# Fit the model
lr.fit(X, y)
# make predictions
pred = lr.predict(X)
Step 9 - Click on Run button.
Step 10 - Click on + sign to create new cell and paste the below code.
features = [[0.06, 14, 6, 0, 0.5, 6, 22, 7, 4, 900, 19, 3690, 8]]
print('The predicted price:', lr.predict(features)[0])
Step 11 - Click on Run button.
See the output.
The predicted price: 40.54991636423439
.