Real-Estate-Price-Prediction

A Machine Learning Project involving Linear Regression Model using Python as the primary Language.

End-to-End Project Idea:

Building a Machine Learning Model(Linear Regression Model) to predict Home prices for several locations.

Writing a Python Flask Server that uses the saved model to serve http requests running in back-end.

Making a user friendly website that gives the estimated prices for different regions.

This project deals with the Data Science Concepts:

• Data load and data Cleaning.
• Feature Engineering.
• One Hot Encoding.
• Outlier Detection.
• Dimentionality Reduction.
• Grid Search CV for hyperparameter tuning.
• K-fold cross validation.

Tools Used

• Jupyter Notebook
• PyCharm
• Git
• Visual Studio Code
• Postman

The necessary Python Libraries to install...

• pandas, numpy, matplotlib [data processing]
• sk learn [model making]
• flask [making the back-end flask server]