https://github.com/umasivakumar14/real_estate_ml_model

Predicts the price of a home in Bengaluru, Karnataka based on location, urbanization, total square feet, bedrooms, bathrooms, and balconies.
https://github.com/umasivakumar14/real_estate_ml_model

flask gridsearchcv http-requests machine-learning machine-learning-algorithms pandas python scikit-learn

Last synced: 3 days ago
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Predicts the price of a home in Bengaluru, Karnataka based on location, urbanization, total square feet, bedrooms, bathrooms, and balconies.

• Host: GitHub
• URL: https://github.com/umasivakumar14/real_estate_ml_model
• Owner: UMASIVAKUMAR14
• Created: 2024-08-02T14:33:10.000Z (3 months ago)
• Default Branch: main
• Last Pushed: 2024-08-05T04:20:35.000Z (3 months ago)
• Last Synced: 2024-10-10T08:02:23.673Z (27 days ago)
• Topics: flask, gridsearchcv, http-requests, machine-learning, machine-learning-algorithms, pandas, python, scikit-learn
• Language: Jupyter Notebook
• Homepage:
• Size: 2.37 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Real_Estate_ML_Model

Interact with the model at http://ec2-3-19-57-187.us-east-2.compute.amazonaws.com/



Used Pandas and Scikit-learn to clean a dataset and develop a ML model that predicted home prices based on location, urbanization, beds, baths, balconies, and sq ft. Trained on a kaggle dataset to 85% accuracy. Built a Python Flask server to respond to HTTP requests. Designed & developed a UI that took user inputs for the model with HTML, CSS, and JavaScript. Configured an Nginx Web Server to handle HTTP requests and serve the website on an AWS EC2 instance. 
Applies concepts learned in code basics machine learning course.