BangaluruHomePricePrediction

This data science project is "real estate price prediction website".

Bangalore Home Prices Data Set used https://www.kaggle.com/datasets/amitabhajoy/bengaluru-house-price-data

We build a model using sklearn and linear regression using banglore home prices dataset from kaggle.com. Second step would be to write a python flask server that uses the saved model to serve http requests. Third component is the website 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 model building we did data loading and cleaning, outlier detection and removal, feature engineering, dimensionality reduction, gridsearchcv for hyperparameter tunning, k fold cross validation.

Python

Numpy and Pandas for data cleaning

Matplotlib for data visualization

Sklearn for model building

Jupyter notebook, visual studio code and pycharm as IDE

Python flask for http server

HTML/CSS/Javascript for UI