ml-project-setup 0.4
A package to auto-generate structured ML project folders
Requires Python: >=3.7

### **📌 Updated `README.md` for `ml_project_setup`**  

```markdown
# 🚀 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.  

---

## 📂 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
```

---

## 🛠 Installation  
Install the package using **pip**:  
```sh
pip install ml_project_setup
```

---

## 🚀 Usage  
To create a new Machine Learning project, run:  
```sh
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:  
```sh
pip install -r requirements.txt
```

---

## 📝 License  
This project is licensed under the **MIT License**. See the [LICENSE](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/](https://pypi.org/project/ml-project-setup/)  
```

---

### **🔹 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**