Update README.md

README.md

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-Hii
 # GridSearchHelper
 
-GridSearchHelper is a Python library designed to simplify hyperparameter tuning using Grid Search. It allows for automatic parameter grid generation and performs efficient grid search for machine learning models. 
+A Python library to simplify hyperparameter tuning using scikit-learn's GridSearchCV. Automate parameter grid generation for various machine learning models and optimize your model's performance with ease.
 
-## Installation
+[![PyPI version](https://badge.fury.io/py/gridsearchhelper.svg)](https://badge.fury.io/py/gridsearchhelper)
+[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
+[![Python 3.6+](https://img.shields.io/badge/python-3.6+-blue.svg)](https://www.python.org/downloads/)
 
-You can install GridSearchHelper from PyPI:
+## 🚀 Quick Start
 
 ```bash
-pip install GridSearchHelper
-=======
-# Hyperparameter Tuning for Classifiers
-
-This project implements a hyperparameter tuning utility for multiple classifiers using `GridSearchCV` from `sklearn`. The supported classifiers include Random Forest, Gradient Boosting, AdaBoost, SVM, K-Nearest Neighbors, Logistic Regression, Decision Trees, Naive Bayes, MLP, and more.
-
-## Features
-- Grid search for hyperparameter optimization on a variety of models.
-- Support for additional custom parameters.
-- Cross-validation (CV) support for model evaluation.
-- Parallel processing for faster results.
-
-## Setup
-1. Clone this repository:
-   ``bash
-   git clone https://github.com/alimovabdulla/GridSearchHelper.git
->>>>>>> 27a8174 (Updated project with new features)
+pip install DridSearchHelper
+```
+
+```python
+from GridSearchHelper import get_param_grid, perform_grid_search
+from sklearn.ensemble import RandomForestRegressor
+
+# Initialize your model
+model = RandomForestRegressor()
+
+# Get parameter grid automatically
+param_grid = get_param_grid(model)
+
+# Perform grid search
+best_params, best_score = perform_grid_search(model, param_grid, X_train, y_train)
+```
+
+## 🔑 Key Features
+
+- 🤖 **Automatic Parameter Grid Generation**: No more manual parameter grid definition
+- 🔄 **Seamless scikit-learn Integration**: Works directly with GridSearchCV
+- 📊 **Multiple Model Support**: Compatible with various scikit-learn models
+- 🛠 **Easy to Use**: Simple API with just two main functions
+
+## 📋 Requirements
+
+- Python 3.6+
+- scikit-learn
+- numpy
+- pandas
+
+## 💻 Installation
+
+### From PyPI
+```bash
+pip install gridsearchhelper
+```
+
+### From Source
+```bash
+git clone https://github.com/alimovabdulla/GridSearchHelper.git
+cd GridSearchHelper
+pip install .
+```
+
+## 📖 Usage Examples
+
+### ElasticNet Example
+
+```python
+from GridSearchHelper import get_param_grid, perform_grid_search
+from sklearn.linear_model import ElasticNet
+from sklearn.preprocessing import StandardScaler
+
+# Prepare your model
+model = ElasticNet(alpha=1)
+
+# Scale your features
+scaler = StandardScaler()
+X_train_scaled = scaler.fit_transform(X_train)
+
+# Get parameter grid and perform search
+param_grid = get_param_grid(model)
+best_params, best_score = perform_grid_search(model, param_grid, X_train_scaled, y_train)
+```
+
+### RandomForest Example
+
+```python
+from GridSearchHelper import get_param_grid, perform_grid_search
+from sklearn.ensemble import RandomForestRegressor
+
+# Initialize model
+model = RandomForestRegressor()
+
+# Get grid and optimize
+param_grid = get_param_grid(model)
+best_params, best_score = perform_grid_search(model, param_grid, X_train, y_train)
+```
+
+## 🛠 API Reference
+
+### get_param_grid(model)
+Generates parameter grid based on model type.
+
+**Parameters:**
+- `model`: scikit-learn model instance
+
+**Returns:**
+- Dictionary containing parameter grid
+
+### perform_grid_search(model, param_grid, X_train, y_train)
+Performs grid search with cross-validation.
+
+**Parameters:**
+- `model`: scikit-learn model instance
+- `param_grid`: Parameter grid dictionary
+- `X_train`: Training features
+- `y_train`: Target values
+
+**Returns:**
+- Tuple of (best_parameters, best_score)
+
+## 🤝 Contributing
+
+Contributions are welcome! Here's how you can help:
+
+1. 🍴 Fork the repository
+2. 🌿 Create a feature branch (`git checkout -b feature/amazing-feature`)
+3. 💻 Make your changes
+4. 📝 Commit your changes (`git commit -m 'Add amazing feature'`)
+5. 📤 Push to the branch (`git push origin feature/amazing-feature`)
+6. 🔄 Open a Pull Request
+
+## 📄 License
+
+This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
+
+## 📞 Contact
+
+Abdullah Alimov - [@alimovabdulla](https://github.com/alimovabdulla)
+
+Project Link: [https://github.com/alimovabdulla/GridSearchHelper](https://github.com/alimovabdulla/GridSearchHelper)
+
+## ⭐️ Show your support
+
+Give a ⭐️ if this project helped you!