House-Price-predictor

ML regression model project to predict house price.

About the project.

In this project I have implemented regression model to predict the house price on giving it required house data.In this project i have implemented two model one is linear model which takes only the house area in sqft and anothoer model is non-linear regression model multiple inputs.In the project i have used sklrean famework to add many functionality to a project which the framework provides.Finaly on predicting the house price the model2 gives more accurate value compared to basic model1.

Used cases

• This project can be integrated to a any service provider which includes selling or buying of the houses.
• This will help the user to set correct price to house if they want to sell the house but dont know how much it worths.
• This will also help the user who wants to buy a house and wants to cross check the price which were given on the plartform.

Technologies used

• Python
• Sklearn ml framework
• Matplotlib graph library
• Numpy for math functions

Project output

>> print("-----------------------------------------------------------------------------------")
>> print("Model 1")
>> print("Actual price = {0} But the model predicted = {1}".format(y_test1[2],y_pred_model1[2]))
>> print("------------------------------------------------------------------------------------")
>> print("Model 2")
>> print("Actual price = {0} But the model predicted = {1}".format(y_test2[0],y_pred_model2[0]))

Result

-----------------------------------------------------------------------------------
Model 1
Actual price = 320000 But the model predicted = 357409.20109429525
------------------------------------------------------------------------------------
Model 2
Actual price = 221000 But the model predicted = 238982.86095643044