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📌 Updated README.md for ml_project_setup

# 🚀 ml_project_setup  
A simple Python package to **automate the creation of structured Machine Learning projects** with a single command.  

## 📖 Overview  
Setting up a clean and organized ML project can be time-consuming. **`ml_project_setup`** makes it effortless by generating the **entire project structure**, including essential files and dependencies.  

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## 📂 Project Structure Created  
When you run `mlsetup my_project`, the following structure is created:  

my_project/ │── source/ │ ├── components/ │ ├── constants/ │ ├── entity/ │ ├── pipeline/ │ ├── utility/ │ ├── exception/ │ ├── logger/ │── data/ # Placeholder for datasets │── models/ # Stores trained models │── notebooks/ # Jupyter notebooks for experiments │── .gitignore # Ignores unnecessary files │── config.yaml # Configuration settings │── Dockerfile # For containerization │── main.py # Entry point script │── README.md # Project documentation │── requirements.txt # Dependencies │── setup.py # Package setup │── setup_env.bat # Windows environment setup │── setup_env.sh # Linux/macOS environment setup


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## 🛠 Installation  
Install the package using **pip**:  
```sh
pip install ml_project_setup

🚀 Usage

To create a new Machine Learning project, run:

mlsetup my_project

This will generate a structured ML project named my_project in the current directory.

➕ Select ML Framework During Setup

You'll be prompted to choose an ML framework, and the package will automatically install it:

🚀 Welcome to ML Project Setup! 🚀
Enter your project name: my_ml_project

Select ML Framework:
[1] scikit-learn (default)
[2] PyTorch
[3] TensorFlow
Enter your choice (1/2/3): 2
📦 Installing PyTorch... This may take a while.
✅ PyTorch installed successfully!
✅ Project 'my_ml_project' created with PyTorch framework!

📦 Dependencies

This package installs dependencies automatically, depending on the framework you select:

Framework Installed Packages
scikit-learn (default) scikit-learn
PyTorch torch, torchvision, torchaudio
TensorFlow tensorflow

If needed, you can manually install dependencies:

pip install -r requirements.txt

📝 License

This project is licensed under the MIT License. See the LICENSE file for details.


👤 Author

Developed by Amogh Pathak
📧 Contact: amogh9792@gmail.com


✨ Contribute & Improve

Have suggestions or feature requests? Feel free to open an issue or contribute on GitHub!

🔗 PyPI: https://pypi.org/project/ml-project-setup/


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### **🔹 What’s Updated?**
✅ **Includes automatic framework installation (scikit-learn, PyTorch, TensorFlow)**  
✅ **Shows example CLI prompt when running `mlsetup`**  
✅ **Lists dependencies based on the selected framework**  

Release files for ml-project-setup 0.4

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