The Algorithms & Data Structures repository is a curated collection of implementations that serve as a foundational resource for understanding and applying core computer science concepts. This project aims to provide clear, practical examples of algorithms and data structures, facilitating both learning and application in real-world scenarios.

Key Components:

• Fundamental Data Structures: Implementations of linked lists, hash tables, stacks, and queues, providing the building blocks for more complex structures and algorithms.
• Sorting Algorithms: A variety of sorting techniques including bubble sort, insertion sort, selection sort, heap sort, merge sort, shell sort, and quick sort, each demonstrating different approaches and efficiencies.
• Tree Structures: Detailed examples of tries, binary search trees (BST), and binary heaps, illustrating hierarchical data organization and manipulation.
• Graph Algorithms: Comprehensive coverage of graph representations and traversals, including single-source shortest path algorithms like Dijkstra and Bellman-Ford, pathfinding with A*, topological sorts using DFS and Kahn's algorithm, and minimum spanning tree algorithms such as Kruskal's and Prim's.
• Techniques: Exploration of recursion and its applications within various algorithms, highlighting its power and versatility.

Each implementation is crafted to be language-agnostic, focusing on the underlying logic and structure, making it accessible to a broad audience regardless of programming background.

This repository is an invaluable tool for students, educators, and professionals seeking to deepen their understanding of algorithms and data structures, offering a practical complement to theoretical study.