https://github.com/alihassanml/car-price-predict-deep-learning
Car Price Predict | Deep Learning Project
https://github.com/alihassanml/car-price-predict-deep-learning
Last synced: 4 months ago
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Car Price Predict | Deep Learning Project
- Host: GitHub
- URL: https://github.com/alihassanml/car-price-predict-deep-learning
- Owner: alihassanml
- Created: 2024-04-09T17:27:40.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-04-09T17:33:44.000Z (over 1 year ago)
- Last Synced: 2025-06-04T02:58:28.826Z (4 months ago)
- Language: Jupyter Notebook
- Size: 1.51 MB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Car-Price-Predict-Deep-Learning
Sure, here is a sample README file for your GitHub repository for your old car price prediction project using TensorFlow deep learning:
---
# Old Car Price Prediction using TensorFlow Deep Learning
This project aims to predict the prices of old cars using deep learning techniques implemented with TensorFlow. It utilizes a dataset containing various features of old cars such as mileage, age, brand, model, etc., to predict their prices accurately.
## Table of Contents
- [Introduction](#introduction)
- [Installation](#installation)
- [Usage](#usage)
- [Dataset](#dataset)
- [Model Architecture](#model-architecture)
- [Results](#results)
- [Contributing](#contributing)
- [License](#license)
## Introduction
The goal of this project is to develop a deep learning model that can accurately predict the prices of old cars based on their characteristics. Predicting old car prices is crucial for both buyers and sellers to make informed decisions. By leveraging deep learning techniques, we aim to build a model that can provide reliable price estimates for old cars.
## Installation
To run this project, you need to have Python installed on your system along with TensorFlow and other required libraries. You can install the dependencies using the following command:
```bash
pip install -r requirements.txt
```
## Usage
To use this project:
1. Clone this repository:
```bash
```
2. Navigate to the project directory:
```bash
cd old-car-price-prediction
```
3. Run the main script:
```bash
python main.py
```
## Dataset
The dataset used for this project contains information about old cars including features like mileage, age, brand, model, etc. It has been preprocessed and cleaned to remove any inconsistencies and missing values. The dataset is divided into training and testing sets for model training and evaluation.
## Model Architecture
The deep learning model architecture consists of several layers including input, hidden, and output layers. The model utilizes TensorFlow's Keras API for building and training the neural network. Various loss functions, optimizers, and metrics are employed to optimize the model and improve its performance.
## Results
The model's performance is evaluated using metrics such as Mean Squared Error (MSE), Mean Absolute Error (MAE), and Root Mean Squared Error (RMSE). Additionally, visualizations such as scatter plots and regression plots are used to analyze the model's predictions and compare them with the actual prices.
## Contributing
Contributions to this project are welcome. You can contribute by:
- Improving the model's architecture.
- Adding new features to enhance prediction accuracy.
- Optimizing code for better performance.
- Fixing any bugs or issues.
Please follow the [contribution guidelines](CONTRIBUTING.md) before making any contributions.
## License
This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
---
Feel free to customize the README according to your project's specifics and add any additional sections or information as needed.