Deploy House Price Prediction Using Flask

Deploy House Price Prediction Using Flask

Deploy House Price Prediction Using Flask - we all known that real estate market is a focused regarding pricing and keep fluctuating, this project help to find a price for property based

In today’s scenario we all known that real estate market is a focused regarding pricing and keep fluctuating . It is the common field that we can apply the ideas of machine learning to enhance the cost with high accuracy . This project help to find a price for property based on the geographical variables by breaking down past market patterns and value ranges and coming advancements future costs will be anticipated.

Project Overview

First of all we have to download dataset from kaggle . Then we have to apply feature engineering into dataset to clean the data , feature scaling , data pre-processing and like many more things . Then we have to divide our dataset into two part , first part says independent feature and dependent feature . In dependent feature we consider price and independent feature consider rest of the column . Then we have to divide dataset into two part, first part train dataset and second part test dataset . Then after we have to apply some regression model to train the data . After that we have test the model and check the accuracy of model .After checking the models I have conclude that the linear regression model is best for this project and the accuracy of the linear regression model is 88% .

Flow Diagram

After creating the model we have to deploy our Linear regression model into web application . For that purpose I have use python framework Flask . Basically Flask has use to connect Linear regression model with HTML , CSS , Javascript code .

After successfully created web application , we have to host our web application . For that I have use Heroku platform . Heroku is use for hosting our web application .

machine-learning deployment-model flask heroku

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