/RealEstate-Estimator

estimate realestate price

Primary LanguageJupyter NotebookMIT LicenseMIT

RealEstate_Fall2023

purpose

usage

run following command and get service running

docker-compose up -d

COPY .env.example to .env

cp .env.example .env

Edit .env and fill fields in the file

visit http://127.0.0.1:8000/ to test if web service is running

visit http://127.0.0.1:8000/docs#/ to see api documentation

check house-price.ipynb to find out the training processes

TODO

  1. write tests
  2. improve data preprocessing
  3. evaluate model
  4. plot metrics

Conclusion

Zillow API would be much suitable for this project becasue the data it provides is more compatible with the training dataset. In contrast, ATTOM API provides free trail api that we can use to implement its APIs in our project. Consequently, this project is currently implementing ATTOM API to get property details.

It is recommended to use Zillow API to get better predictions.