This repository contains a diamond price prediction project for predicting the price of diamonds using the datasets input features : Carat, Depth, Table, x, y, z, Cut, Color and Clarity.
Data set Link : https://www.kaggle.com/competitions/playground-series-s3e8/data?select=train.csv Dataset Information : Available in EDA under the notebooks folder
This project is a an example of Regression Problem. We have used multiple Regression algorithms and the best algorithm is used for the prediction.
List of models the project uses to train on the dataset -
- Linear Regression
- Lasso
- Ridge
- Elastic Net
- Random Forest
- Decision Tree
To get started with this project, follow these steps:
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Clone the repository to your local machine using the following command: git clone https://github.com/Sumeetparmar0/DiamondPricePrediction1.git
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Navigate to the project directory: cd DiamondPricePrediction1
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Install the required dependencies using pip: pip install -r requirements.txt
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Run the Flask application: python application.py
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Open your web browser and go to http://127.0.0.1:5000/ - to access the home page
http://127.0.0.1:5000/predict - to perform prediction of diamond price on the web application.