Gemstone Price Prediction

Project Overview

his project aims to predict the price of gemstones using various machine learning algorithms and operationalizing the model. It aim to predict the price of gemstones based on various factors such as carat, depth, table, dimensions, cut, color, and clarity. By leveraging historical data on gemstone attributes and prices, we can develop machine learning models to accurately predict the price of gemstones, thereby assisting gemstone traders and buyers in making informed decisions.

Objectives

1. Develop machine learning models to predict gemstone prices based on their attributes.
2. Implement best practices in machine learning operations (MLOps) to ensure the scalability, reproducibility, and reliability of the prediction pipeline.
3. Deploy the trained models to production environments for real-time price predictions.

How to Use This Repository

1. Clone the repository to your local machine.
2. Install the required dependencies specified in the requirements.txt file.
3. Explore the project structure to understand the organization of code, data, and resources.
4. Follow the instructions in the README.md file to run the prediction pipeline and deploy the models to production environments.

Getting Started

-- To run this project on your local machine, follow these steps:

1. Clone the Repository:

   https://github.com/Saurabh932/Gemstome_Price_Prediction.git/

   cd gemstone-price-prediction

   
   

2. Install Dependencies:

   pip install -r requirements.txt

   
   

3. Run the Application: To run the Flask web application:

   python app.py

• Access the application in your web browser at http://localhost:8000.

Techstack Used:

• Python
• Git
• DVC
• Flask
• MLFlow
• Docker

Web Application Demo

1. Click the button to procedded:

2. Enter the values.

3. Click on submit to get final Result