Car price prediction using Machine learning python

This blog contains the source code for Machine learning project car price prediction using python.

Step 1: Installing libraries

*pip install numpy

*pip install pandas

*pip install sklearn

Step 2: Importing the libraries

import pandas as pd

import numpy as np

from sklearn import linear_model

Step 3: Reading the CSV

df=pd.read_csv('car_data.csv')

df

Step 4: Preprocessing 1:

inputs=df.drop(['Car_Name','Owner','Seller_Type'],axis='columns') 

target=df.Selling_Price

inputs

Step 5: Preprocessing 2

from sklearn.preprocessing import LabelEncoder

Numerics=LabelEncoder()

inputs['Fuel_Type_n']=Numerics.fit_transform(inputs['Fuel_Type'])

inputs['Transmission_n']=Numerics.fit_transform(inputs['Transmission'])

inputs

Step 6: Dropping the string columns

inputs_n=inputs.drop(['Fuel_Type','Transmission','Selling_Price'],axis='columns') 

inputs_n

Step 7: Implemention of Linear regression & Prediction

model=linear_model.LinearRegression()

model.fit(inputs_n,target)

pred=model.predict([[2013,9.54,430000,1,1]])

Fullcode: Github

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