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Releases: thomasthaddeus/AlgorithmSelector

Update Documentation

30 Dec 20:00
@thomasthaddeus thomasthaddeus
v1.1.0
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Fixing the tag number of the release to 1.1.0

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v1.0.0 Release

25 Dec 05:47
@thomasthaddeus thomasthaddeus
v1.0.0
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v1.0.0 Release

Release Notes for AlgorithmSelector v1.0.0

We are excited to announce the release of AlgorithmSelector v1.0.0. This marks a significant milestone in our project, bringing together a diverse and comprehensive collection of algorithms and data structures. This version is the culmination of dedicated efforts in creating a robust, efficient, and educational resource for both enthusiasts and professionals in the field of computer science.

What's New in v1.0.0

  • Broad Range of Algorithms: Includes a variety of algorithms from computational methods, data structures, cryptographic techniques, to machine learning models.
  • Enhanced Data Structures: Implementations of essential data structures like AVL Trees, Heaps, Tries, and more, optimized for performance and usability.
  • Machine Learning and AI Integration: Introduction of foundational machine learning algorithms and AI strategies, including k-means clustering and linear regression models.
  • Comprehensive Cryptographic Methods: Robust cryptographic algorithms such as AES and RSA for enhanced data security.
  • Advanced Computational Algorithms: Implementation of complex algorithms like Fast Fourier Transform and Monte Carlo simulations.
  • Graph Theory and Network Flow: Features graph analysis and network flow algorithms, including Dijkstra's, Kruskal's, and Ford-Fulkerson methods.
  • User-Friendly Documentation: Detailed documentation and usage examples for each algorithm, ensuring ease of understanding and implementation.

Improvements

  • Refined codebase with improved readability and performance optimizations.
  • Comprehensive unit tests covering a wide range of scenarios to ensure reliability.
  • Streamlined build and deployment process with integrated Poetry and setuptools support.
  • Enhanced documentation for better clarity and guidance.

Breaking Changes

  • Transitioned to pyproject.toml for project configuration and dependency management, moving away from setup.py.
  • Standardized directory structure for more intuitive navigation and usage.

Acknowledgments

We want to thank all the contributors who have dedicated their time and expertise to make this project successful. Your contributions, big and small, have been invaluable.

How to Get Started

To get started with AlgorithmSelector v1.0.0, please refer to our GitHub repository for detailed instructions on installation, usage, and contribution.

Feedback and Contributions

We are committed to continuously improving AlgorithmSelector and we welcome your feedback and contributions. For any suggestions, issues, or if you would like to contribute, please visit our GitHub Issues page.

Thank you for your support and we hope you enjoy using AlgorithmSelector v1.0.0!

AlgorithmSelector v1.0.0 - released on 12-24-2023

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