/House-Price-Prediction

The house price was estimated based on the user's choices. Xgboost was used for training the model and Streamlit was used for deployment.

Primary LanguagePython

House Price Prediction Project

Open in Streamlit

https://share.streamlit.io/enesbol/streamlitrepo/main/HousePrice.py

Description

This project is a part of K136. Kodluyoruz & Istanbul Metropolitan Municipality Data Science Bootcamp.The model is trying to estimate the house prices related to users choices.

Data

The dataset is available at Kaggle.

Project's Steps:

⚪️ Data was downloaded from kaggle and readed.

⚪️ Data is cleaned and get ready for model.

⚪️ Data was trained with XGBoost Regression Model.

⚪️ UI design with Streamlit

⚪️ Deploy with Streamlit Cloud

Contributions