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Algorithms related to: Machine learning, Deep learning, Networks, Graph Theory, Trees, Heaps, Sorting, Searching, Scientific computations, Metaheuristic, Probabilistic, Number Theory, String & text processing, AI, Robotics & Pathfinding, Big Data & Cloud Computing,

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🧠 Algorithms Hub

Welcome to Algorithms Hub – a curated and comprehensive collection of algorithms and implementations across core computer science and engineering domains including Machine Learning, Deep Learning, Cloud Computing, Data Structures, and more.

This repository serves as both a reference and learning tool for students, developers, and researchers.


📁 Repository Structure

This repository is organized into clearly labeled folders for each domain. Each contains well-structured code, readable implementations, and supporting documentation or comments when needed.


🚀 What You'll Find

✅ Machine Learning

  • Linear & Logistic Regression
  • K-Nearest Neighbors (KNN)
  • Support Vector Machines (SVM)
  • Naive Bayes Classifier
  • Decision Trees and Random Forests
  • Clustering Algorithms (K-Means, DBSCAN)
  • Gradient Boosting (XGBoost, LightGBM)

✅ Deep Learning

  • Feedforward Neural Networks (FNN)
  • Convolutional Neural Networks (CNN)
  • Recurrent Neural Networks (RNN, LSTM, GRU)
  • Transfer Learning with Pretrained Models
  • Backpropagation and Activation Functions

✅ Cloud Computing

  • Load Balancing Algorithms (Round Robin, Least Connection, Weighted)
  • Autoscaling Simulators
  • Task Scheduling in Distributed Environments
  • Cloud Storage Optimization
  • Container Orchestration Concepts (Docker, Kubernetes simulations)

✅ Data Structures

  • Arrays, Linked Lists (Singly/Doubly)
  • Stacks and Queues
  • Trees (Binary Trees, AVL Trees, Tries)
  • Graph Algorithms (BFS, DFS, Dijkstra, A*)
  • Hash Tables, Heaps (Min/Max), Priority Queues
  • Disjoint Sets, Union-Find

🛠️ Technologies Used

  • Languages: Python, Java, C++, JavaScript
  • Libraries:
    • ML/DL: NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch, Matplotlib
    • Cloud: Docker, Flask (simulations), YAML configs
    • Utilities: Jupyter Notebooks, Git, VSCode

🧪 How to Use

  1. Clone the repository:
    git clone https://github.com/your-username/algorithms-hub.git
    cd algorithms-hub

🧑‍💻 Contribution Guidelines Contributions are highly appreciated! Here's how you can help:

🐞 Fix issues or bugs

📚 Improve documentation

✨ Add new algorithms or enhance existing ones

🧪 Add tests or examples

Steps to Contribute Fork this repository

Create a new branch: git checkout -b feature-name

Commit your changes: git commit -m "Add feature"

Push to the branch: git push origin feature-name

Open a Pull Request

📜 License This repository is licensed under the MIT License. See the LICENSE file for more information.

🙌 Acknowledgments Thanks to the open-source community for inspiration and foundational knowledge.

Special credit to contributors who help expand this resource every day.

⭐️ Show Your Support If you find this project helpful or interesting:

🌟 Give it a star

🍴 Fork it and build on it

🧠 Share it with your peers


Let me know if you'd like:

  • Shields/badges added (e.g. for license, stars, forks)
  • GitHub Pages documentation
  • Separate sections for each language (e.g., Python-only folder)
  • Automatic testing or GitHub Actions integration

I can generate those too.

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Algorithms related to: Machine learning, Deep learning, Networks, Graph Theory, Trees, Heaps, Sorting, Searching, Scientific computations, Metaheuristic, Probabilistic, Number Theory, String & text processing, AI, Robotics & Pathfinding, Big Data & Cloud Computing,

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