House Price Prediction Using Machine Learning

Our goal focused on solving the problem of predicting house prices for house buyers .A house value is simply more than location and square footage. Like the features that make up a person, an educated party would want to know all aspects that give a house its value. We are going to take advantage of

2025-06-28 16:32:57 - Adil Khan

Project Title

House Price Prediction Using Machine Learning

Project Area of Specialization Artificial IntelligenceProject Summary

Our goal focused on solving the problem of predicting house prices for house buyers .A house value is simply more than location and square footage. Like the features that make up a person, an educated party would want to know all aspects that give a house its value. We are going to take advantage of all of the feature variables available to use and use it to analyze and predict house prices. Our goal for this project was to use regression techniques in order to estimate the price of a house in Sialkot given the feature and pricing data for around 1000+ houses sold.

Ask a home buyer to describe their dream house, and they probably won't begin with the height of the basement ceiling or the proximity to an east-west railroad. But this playground competition's dataset proves that much more influences price negotiations than the number of bedrooms or a white-picket fence

Project Objectives Project Implementation Method

We are using softwares are pycharm ,android SDK is being used for house price prediction . we are using java  language and also XML language used for front end design.we will dsign our interface in XML.And also use java language use for training a Machine learning model to predict house price prediction.

Benefits of the Project

We will provide the facilities to the user and user tell some feature about house then we will use the machine learning techniques and algorithms to tell the user. Now, they want to know if the house price matches the house value.

Users can understand which features (ex. Number of bathrooms, location, etc.) Influence the final price of the house. If all matches, they can ensure that they are getting a fair price

Technical Details of Final Deliverable

First of all user have to register his self or not.Then the Android app will select the option within

We will provide the facilities to the user and user tell some feature about house then we will use the machine learning techniques and algorithms to tell the user. Now, they want to know if the house price matches the house value.

Users can understand which features (ex. Number of bathrooms, location, etc.) Influence the final price of the house. If all matches, they can ensure that they are getting a fair price

Final Deliverable of the Project Software SystemCore Industry ITOther Industries Others Core Technology Artificial Intelligence(AI)Other Technologies OthersSustainable Development Goals No PovertyRequired Resources
Item Name Type No. of Units Per Unit Cost (in Rs) Total (in Rs)
Total in (Rs) 20
hous Miscellaneous 4520

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