https://github.com/abhisek-13/multi-commodity-price-predictor
The Multi-Commodity Price Predictor is a machine learning project that predicts the prices of cars, bikes, and laptops. Using advanced techniques, it provides accurate price predictions based on user inputs. The project features an easy-to-use interface built with Streamlit, enabling users to get price predictions quickly and easily.
https://github.com/abhisek-13/multi-commodity-price-predictor
machine-learning machine-learning-algorithms matplotlib numpy pandas python seaborn sklearn sklearn-library streamlit
Last synced: 3 months ago
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The Multi-Commodity Price Predictor is a machine learning project that predicts the prices of cars, bikes, and laptops. Using advanced techniques, it provides accurate price predictions based on user inputs. The project features an easy-to-use interface built with Streamlit, enabling users to get price predictions quickly and easily.
- Host: GitHub
- URL: https://github.com/abhisek-13/multi-commodity-price-predictor
- Owner: abhisek-13
- Created: 2023-08-16T13:40:26.000Z (almost 3 years ago)
- Default Branch: main
- Last Pushed: 2024-07-01T09:12:06.000Z (almost 2 years ago)
- Last Synced: 2025-02-03T11:17:36.327Z (over 1 year ago)
- Topics: machine-learning, machine-learning-algorithms, matplotlib, numpy, pandas, python, seaborn, sklearn, sklearn-library, streamlit
- Language: Python
- Homepage:
- Size: 5.01 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Multi-Commodity Price Predictor
## Overview
The Multi-Commodity Price Predictor is a machine learning project designed to predict the prices of various commodities, specifically cars, bikes, and laptops. This project leverages advanced machine learning techniques to provide accurate price predictions based on user inputs. The project includes a user-friendly interface built with Streamlit, allowing users to interact with the model and obtain price predictions for each commodity.
## Features
- **Car Price Prediction:** Input car-specific details and get an estimated price.
- **Bike Price Prediction:** Input bike-specific details and get an estimated price.
- **Laptop Price Prediction:** Input laptop-specific details and get an estimated price.
- **Streamlit Interface:** A clean and intuitive interface for each commodity, making it easy for users to input data and view predictions.
## Technologies Used
- **Python:** Programming language used for model development.
- **Machine Learning:** Algorithms and models for price prediction.
- **Streamlit:** Framework for building the user interface.
## Installation
1. Clone the repository:
```bash
git clone https://github.com/yourusername/multi-commodity-price-predictor.git
cd multi-commodity-price-predictor
```
2. Create and activate a virtual environment:
```bash
python -m venv venv
venv\Scripts\activate # On Windows
```
3. Install the required packages:
```bash
pip install -r requirements.txt
```
## Usage
1. Run the Streamlit application:
```bash
streamlit run multiCP.py
```
2. Open the provided local URL in your web browser.
## Project Structure
- `app.py`: Main application file for running the Streamlit interface.
- `models/`: Directory containing the machine learning models for each commodity.
- `data/`: Directory containing any datasets used for training the models.
- `requirements.txt`: List of dependencies required to run the project.
## How to Use
1. Open the application in your browser.
2. Select the commodity (Car, Bike, or Laptop) from the interface.
3. Input the required details specific to the selected commodity.
4. Click on the 'Predict' button to get the estimated price.
## Contributing
Contributions are welcome! Please fork the repository and submit a pull request for any enhancements or bug fixes.
## License
This project is licensed under the MIT License. See the `LICENSE` file for more details.
## Contact
For any questions or feedback, please contact [abhisekmaharana9861@gmail.com](abhisekmaharana9861@gmail.com).