Remove redundant sections from README.md

Removed sections on Table of Contents, About, Features, and Contributing from README.

Author: cclauss

README.md

@@ -36,149 +36,14 @@
 
 Implementations are for learning purposes only. They may be less efficient than the implementations in the Python standard library. Use them at your discretion.
 
-## � Table of Contents
-
-- [About](#-about)
-- [Features](#-features)
-- [Getting Started](#-getting-started)
-  - [Installation](#installation)
-  - [Usage](#usage)
-- [Algorithm Categories](#-algorithm-categories)
-- [Community Channels](#-community-channels)
-- [Contributing](#-contributing)
-- [License](#-license)
-- [List of Algorithms](#-list-of-algorithms)
-
-## � About
-
-This repository contains Python implementations of various algorithms and data structures for educational purposes. Whether you're a student learning algorithms, a developer preparing for technical interviews, or someone interested in computer science fundamentals, this collection provides clear and well-documented examples.
-
-## ✨ Features
-
-This repository includes implementations of algorithms across multiple categories:
-
-- **Sorting Algorithms**: Bubble sort, Quick sort, Merge sort, Heap sort, and more
-- **Searching Algorithms**: Binary search, Linear search, Jump search, Interpolation search
-- **Data Structures**: Linked lists, Stacks, Queues, Trees, Graphs, Hash tables
-- **Graph Algorithms**: BFS, DFS, Dijkstra's algorithm, Floyd-Warshall, Bellman-Ford
-- **Dynamic Programming**: Knapsack, Longest Common Subsequence, Edit Distance
-- **Machine Learning**: Neural networks, Linear regression, K-means clustering
-- **Mathematical Algorithms**: Prime number algorithms, GCD, LCM, Number theory
-- **String Algorithms**: Pattern matching, String manipulation, Parsing
-- **Cryptography**: Various cipher implementations
-- **Computer Vision**: Image processing algorithms
-- **And many more!**
-
-All implementations include:
-
-- Clear documentation and explanations
-- Type hints for better code readability
-- Doctests for validation
-- Educational comments
-
 ## 🚀 Getting Started
 
-### Installation
-
-1. **Clone the repository**
-
-   ```bash
-   git clone https://github.com/TheAlgorithms/Python.git
-   cd Python
-   ```
-
-2. **Set up a virtual environment (recommended)**
-
-   ```bash
-   python -m venv venv
-
-   # On Windows
-   venv\Scripts\activate
-
-   # On macOS/Linux
-   source venv/bin/activate
-   ```
-
-3. **Install dependencies**
-
-   ```bash
-   pip install -r requirements.txt
-   ```
-
-### Usage
-
-Each algorithm is self-contained in its own file. You can run any algorithm directly or import it into your own projects.
-
-**Example 1: Running an algorithm directly**
-
-```bash
-python sorts/quick_sort.py
-```
-
-**Example 2: Importing and using an algorithm**
-
-```python
-from sorts.quick_sort import quick_sort
-
-# Sort a list
-numbers = [64, 34, 25, 12, 22, 11, 90]
-sorted_numbers = quick_sort(numbers)
-print(sorted_numbers)  # Output: [11, 12, 22, 25, 34, 64, 90]
-```
-
-**Example 3: Running doctests**
-
-```bash
-python -m doctest -v sorts/bubble_sort.py
-```
-
-## 📂 Algorithm Categories
-
-For a complete list of all implemented algorithms organized by category, see our [DIRECTORY.md](DIRECTORY.md) file.
+📋 Read through our [Contribution Guidelines](CONTRIBUTING.md) before you contribute.
 
 ## 🌐 Community Channels
 
 We are on [Discord](https://the-algorithms.com/discord)! Community channels are a great way for you to ask questions and get help. Please join us!
 
-## 🤝 Contributing
-
-We welcome contributions from the community! Before contributing:
-
-1. 📋 Read through our [Contribution Guidelines](CONTRIBUTING.md)
-2. 🔍 Check existing implementations to avoid duplicates
-3. ✅ Ensure your code follows our coding standards
-4. 🧪 Include doctests and proper documentation
-5. 🎯 Make sure all tests pass before submitting
-
-**Quick Start for Contributors:**
-
-```bash
-# Install pre-commit hooks
-pip install pre-commit
-pre-commit install
-
-# Run tests
-python -m pytest
-
-# Format code
-pip install ruff
-ruff check
-```
-
-Contributions that are most welcome:
-
-- New algorithm implementations
-- Improvements to existing algorithms
-- Better documentation and explanations
-- Bug fixes
-- Test coverage improvements
-
-## 📄 License
-
-This project is licensed under the [MIT License](LICENSE.md) - see the [LICENSE.md](LICENSE.md) file for details.
-
-This means you are free to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the software.
-
 ## 📜 List of Algorithms
 
 See our [directory](DIRECTORY.md) for easier navigation and a better overview of the project.