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Boston house price prediction using Linear regression.
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You want to be the best real estate agent out there. In order to compete with other agents in your area, you decide to use machine learning. You are going to use various statistical analysis tools to build the best model to predict the value of a given house. Your task is to find the best price your client can sell their house at. The best guess from a model is one that best generalizes the data.
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Live Demo: https://house-price-prediction2020.herokuapp.com/predict
git clone chicks2014/Boston_house_price_prediction
- Python >= 3.6
- Python Libraies:
scikit-learn, numpy, pandas, scipy, click, Flask, Flask-Cors, Jinja2, requests, urllib3
- pip install -r requirements.txt
- Flask is a light-weight web framework for Python
- Easy to work with (Same syntax as of Python)
- While Flask addresses itself as a "micro-framework", it is not lacking in features or power, especially with a clutch of extensions to support features such as authentication, databases and so on
- Comprehensive documentation available