https://github.com/madhu-smita-behera/bangalore-house-price-prediction-model

Predicting the house prices of Bangalore city with 2017 data
https://github.com/madhu-smita-behera/bangalore-house-price-prediction-model

Last synced: 7 days ago
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Predicting the house prices of Bangalore city with 2017 data

• Host: GitHub
• URL: https://github.com/madhu-smita-behera/bangalore-house-price-prediction-model
• Owner: madhu-smita-behera
• License: apache-2.0
• Created: 2024-06-02T11:57:58.000Z (6 months ago)
• Default Branch: main
• Last Pushed: 2024-06-03T16:43:41.000Z (6 months ago)
• Last Synced: 2024-06-04T14:08:43.976Z (5 months ago)
• Language: Jupyter Notebook
• Homepage:
• Size: 7.18 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# Bangalore-House-Price-Prediction

The Bangalore House Price Prediction project aims to build a machine learning model that accurately predicts residential property prices in Bangalore. The project follows a systematic approach, starting with data collection and preprocessing.

### EDA

Data preprocessing involves handling missing values, encoding categorical variables, and normalizing numerical features. Exploratory Data Analysis (EDA) helps in understanding data distributions and relationships between features, using visualizations to identify trends and patterns. Feature engineering is performed to create new relevant features from existing data, such as price per square foot. The dataset is then split into training and testing sets to evaluate model performance.

### Model Evaluation

Several regression algorithms are experimented with, including Linear Regression, Random Forest. The best performing model is selected based on metrics like root mean square error and r2_score.

### Conclusion

Among both the models, random forest showed lesser rmse and more r2_score indicating to be a better model for this dataset.

### Prediction

The web application provides a user-friendly interface for predicting house prices in Bangalore based on several input features. 

Check this screenshot of how the webpage looks like: