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# Skunks Skool
Skunks Skool Tutorials
# Algorithm Analysis and Complexity

## Introduction
This repository is dedicated to the study and analysis of algorithms and their complexity. Understanding algorithmic design and analysis is essential for developing efficient and effective solutions to a wide range of computational problems.

## Table of Contents
1. [Algorithm Analysis](#algorithm-analysis)
2. [Complexity Analysis](#complexity-analysis)
3. [Stable Matching](#stable-matching)
4. [Contributing](#contributing)
5. [License](#license)

## Algorithm Analysis
In this section of the repository, you will find materials and resources related to the analysis of algorithms. This includes:

- **Big O Notation**: Explanation and examples of Big O notation, which is used to describe the upper bound on the time complexity of an algorithm.

- **Time and Space Complexity**: Discussions on time complexity, space complexity, and their analysis.

- **Asymptotic Analysis**: Exploring how algorithms behave as input size approaches infinity and how this analysis helps us compare and classify algorithms.

## Complexity Analysis
This section focuses on the analysis of algorithmic complexity. It includes:

- **Worst-case, Best-case, and Average-case Analysis**: Understanding the differences between these types of complexity analysis and when to use them.


- **Practical Examples**: Real-world examples of algorithm complexity analysis, helping you apply these concepts to actual problems.

## Stable Matching
Stable matching is a specific problem in the domain of algorithmic problems. In this section, you will find information on:

- **Stable Marriage Problem**: Explanation and implementation of the stable marriage problem, a classic problem in matching theory.

- **Applications**: Discussing real-world applications of stable matching, such as in online dating algorithms and hospital-resident matching.

## Contributing
We welcome contributions from the community to enrich the resources in this repository. If you have algorithm analysis techniques, complexity analysis examples, or additional content related to stable matching that you'd like to share, please feel free to create a pull request. Check out our [contributing guidelines](CONTRIBUTING.md) for more details.

## License
This repository is open-source and available under the [MIT License](LICENSE). Please review the license file for more information about how you can use and distribute the contents of this repository.

Thank you for being a part of our algorithm analysis and complexity community! We hope you find the resources here valuable in your journey to mastering algorithms and their analysis.