This project is Data Science Real Estate price prediction Project. Firstly, the model was built using sklearn and linear regression using banglore home prices dataset from kaggle.com. Secondly, i wrote a python flask server that uses the saved model to serve http requests. Thirdly, a website was built in html, css and javascript that allows user to enter home square ft area, bedrooms etc and it will call python flask server to retrieve the predicted price. During the model building, i covered almost all data science concepts such as data load and cleaning, outlier detection and removal, feature engineering, dimensionality reduction, gridsearchcv for hyperparameter tunning, k fold cross validation etc.
The Technology used are:
- python
- jypyter Notebook, visual studio code as IDE
- Numpy and pandas for data Clearning
- Matplotlib for data Visualization
- Sklearn for model building
- python flask for http server
- HTML/CSS, Javascript for UI