This is basically a real estate price prediction website build using Machine Learning on a python flask server that uses the saved model to serve http requests.
The ML model uses data load and cleaning, outlier detection and removal, feature engineering, dimensionality reduction, gridsearchcv for hyperparameter tunning, k fold cross validation etc.
The UI is built using HTML, CSS, JavaScript where we have used JQuery to connect the flask server with frontend of Website.
The Website is Deployed on Amazon EC2 instance cloud server (Ubuntu) alongside with Nginx Open-source Web Sevrer using Revrse Proxy.
- Python
- Numpy and Pandas for data cleaning
- Matplotlib for data visualization
- Sklearn for model building
- Jupyter notebook, visual studio code as IDE
- Python flask for http server
- HTML/CSS/Javascript for UI
- JQuery
- Nginx
- Amazon EC2 Instance Cloud Server for Deployment