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Model deployment with flask api, using Linear Regression to predict the price value. Deploy ML Models Using Flask to take your models from python to production.

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JafirDon/House-price-prediction-using-flask

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House-price-prediction-using-flask

This project demonstrates the predictive capabilities of a model trained on house price data using Linear Regression. The model is deployed using a Flask API, providing an interface to predict house prices based on input features.

For a detailed explanation, check out my blog post: House Price Prediction using Flask for Beginners

Installation

You'll need to install the required libraries to run this web app on your local machine. These are listed in the requirements.txt file. The project was developed using Python 3.8.0 and Flask 2.0.1.

Install the necessary packages by running the following command in your terminal:

pip install -r requirement.txt


Getting Started

After installing the required packages, you can start the application by executing the following command in your terminal:

python app.py


Preview





License

MIT License

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Model deployment with flask api, using Linear Regression to predict the price value. Deploy ML Models Using Flask to take your models from python to production.

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