https://github.com/nour-awawdeh/introductiontoalgorithms

C# & Algorithm
https://github.com/nour-awawdeh/introductiontoalgorithms

algorithms algorithms-and-data-structures csharp-code

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C# & Algorithm

• Host: GitHub
• URL: https://github.com/nour-awawdeh/introductiontoalgorithms
• Owner: NOUR-AWAWDEH
• Created: 2024-07-29T11:31:59.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2024-08-15T03:48:29.000Z (over 1 year ago)
• Last Synced: 2025-01-20T06:43:35.164Z (11 months ago)
• Topics: algorithms, algorithms-and-data-structures, csharp-code
• Language: C#
• Homepage:
• Size: 348 KB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
# Introduction to Algorithms - 4th Edition

This repository contains explanations and implementations of the algorithms covered in the 4th edition of the "Introduction to Algorithms" book by Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, and Clifford Stein.

## About the Book

"Introduction to Algorithms" is a comprehensive textbook that covers a wide range of fundamental algorithms and data structures. It is widely regarded as one of the most important works in computer science and is used in many university courses around the world.

## Purpose of this Repository

The goal of this repository is to provide clear and concise explanations of the algorithms presented in the book, along with C# implementations to help readers understand the concepts more easily.

## Contents

The repository is organized into the following 8 parts, each covering different topics and chapters from the book:

1. **Part I: Foundations**

   - Chapter 1: The Role of Algorithms in Computing

   - Chapter 2: Getting Started

   - Chapter 3: Characterizing Running Times

   - Chapter 4: Divide-and-Conquer

   - Chapter 5: Probabilistic Analysis and Randomized Algorithms

2. **Part II: Sorting and Order Statistics**

   - Chapter 6: Heapsort

   - Chapter 7: Quicksort

   - Chapter 8: Sorting in Linear Time

   - Chapter 9: Medians and Order Statistics

3. **Part III: Data Structures**

   - Chapter 10: Elementary Data Structures

   - Chapter 11: Hash Tables

   - Chapter 12: Binary Search Trees

   - Chapter 13: Red-Black Trees

4. **Part IV: Advanced Design and Analysis Techniques**

   - Chapter 14: Dynamic Programming

   - Chapter 15: Greedy Algorithms

   - Chapter 16: Amortized Analysis

5. **Part V: Advanced Data Structures**

   - Chapter 17: Augmenting Data Structures

   - Chapter 18: B-Trees

   - Chapter 19: Data Structures for Disjoint Sets

6. **Part VI: Graph Algorithms**

   - Chapter 20: Elementary Graph Algorithms

   - Chapter 21: Minimum Spanning Trees

   - Chapter 22: Single-Source Shortest Paths

   - Chapter 23: All-Pairs Shortest Paths

   - Chapter 24: Maximum Flow

   - Chapter 25: Matchings in Bipartite Graphs

7. **Part VII: Selected Topics**

   - Chapter 26: Parallel Algorithms

   - Chapter 27: Online Algorithms

   - Chapter 28: Matrix Operations

   - Chapter 29: Linear Programming

   - Chapter 30: Polynomials and the FFT

   - Chapter 31: Number-Theoretic Algorithms

   - Chapter 32: String Matching

   - Chapter 33: Machine-Learning Algorithms

   - Chapter 34: NP-Completeness

   - Chapter 35: Approximation Algorithms

8. **Part VIII: Appendix**

   - Appendix A: Summations

   - Appendix B: Sets, Etc.

   - Appendix C: Counting and Probability

   - Appendix D: Matrices

Each part and chapter includes detailed explanations of the algorithms, their time and space complexities, and C# implementations to demonstrate the concepts.

## How to Use This Repository

1. Clone the repository to your local machine:

2. Read the chapter notes in the repository before reading the corresponding chapter in the book.

   By reading the chapter notes first, you can get a high-level understanding of the concepts and algorithms covered in the book. This will help you better contextualize the information when you read the book and make the learning process more efficient.

3. Explore the C# implementations for each algorithm and data structure.

   The C# code provided in the repository can help you visualize and better understand the algorithms. Feel free to experiment with the code, modify it, and try to solve additional problems from the book.

4. If you have any questions or need further clarification, use the repository's issue tracker to ask for help.

5. Consider contributing to the repository by adding new content, fixing bugs, or improving existing explanations.

## Pre-Requisite Knowledge

1. **Pre-Algebra**: [Pre-Algebra](https://youtu.be/VXzm8ReImG0?si=cSyK1MZU-H5AkCJA) - Covers foundational mathematics concepts including basic arithmetic, fractions, and introductory algebra.

2. **Algebra **: [Algebra](https://youtu.be/GAN-jgzYsIo?si=uyfvkKZOZIKo5z-d) - Introduces variables, equations, functions, and basic graphing.

3. **College Algebra**: [College Algebra](https://youtu.be/LwCRRUa8yTU?si=UYvIitSWMl_ujSw2) - Explores advanced algebraic concepts including polynomial, rational, exponential, and logarithmic functions.

4. **Precalculus**: [Precalculus](https://youtu.be/eI4an8aSsgw?si=fJKpfBsRft0rHPBQ) - Prepares students for calculus by covering functions, complex numbers, trigonometry, and analytical geometry.

5. **Calculus 1**: [Calculus 1](https://youtu.be/HfACrKJ_Y2w?si=TFr8A93DEuF02uPD) - Focuses on limits, derivatives, and integrals of single-variable functions.

6. **Calculus 2**: [Calculus 2](https://youtu.be/7gigNsz4Oe8?si=v38qCTvVOYEvhgmx) - Continues calculus studies with techniques of integration, series, and polar coordinates.

7. **Discrete Mathematics**: [Discrete Mathematics](https://www.youtube.com/watch?v=A3Ffwsnad0k&list=PLl-gb0E4MII28GykmtuBXNUNoej-vY5Rz) - Covers logic, set theory, combinatorics, graph theory, and algorithms.

8. **Linear Algebra**: [Linear Algebra](https://youtu.be/JnTa9XtvmfI?si=cfdcPMjwTdz5zIMD) - Discusses vector spaces, matrices, determinants, eigenvalues, and eigenvectors.

9. **Introduction to probability** : [Introduction to probability](https://youtube.com/playlist?list=PLUl4u3cNGP60hI9ATjSFgLZpbNJ7myAg6&si=iZ9GFfkfxRen1h4w) - Introduces probability theory.

10. **Statistics**: [Statistics](https://youtu.be/LJa4_yGOmwo?si=1ST5GE_4_hfxpv1u) - Introduces statistical methods, and data analysis techniques.

11. **Basic C# Langague Knowlege**: [C# Course](https://youtu.be/M5ugY7fWydE?si=LHdc7iQuPUgyX_4f) - Introduction to C# Langauge.

If you have a good  math skills you can just try MIT course:  [Mathematics for Computer Science](https://youtube.com/playlist?list=PLB7540DEDD482705B&si=pN9GfqvaPwvl-cY4)

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By following these steps, you can effectively use this repository to supplement your learning from the "Introduction to Algorithms 4th" book and gain a deeper understanding of the concepts through the provided C# implementations.

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