This repository provides the code and explanations for "50 Algorithms Every Programmer Should Know - Second Edition," a book aimed at developers seeking to understand and apply algorithms to real-world problems. It covers a broad spectrum of algorithms, from fundamental data structures and sorting to advanced deep learning and LLM architectures, offering practical Python implementations and cloud-based notebook execution.

How It Works

The project is structured around the book's chapters, with each chapter focusing on a specific algorithmic domain. It utilizes Python for implementation, with many examples provided as Jupyter notebooks runnable on Google Colab or Kaggle. The approach emphasizes understanding the "why" behind algorithms, their design principles, and practical application through case studies, including areas like graph analysis for fraud detection, recommendation engines, and cryptography.

Quick Start & Requirements

• Install/Run: Execute provided Jupyter notebooks via Google Colab or Kaggle.
• Prerequisites: A web browser and internet connection are sufficient for cloud execution. Local execution requires a Python environment.
• Setup: Instantaneous via cloud platforms.
• Links: Google Colab, Kaggle

Highlighted Details

• Comprehensive coverage from basic data structures to LLMs.
• Practical examples for fraud detection, recommendation engines, and NLP.
• Focus on algorithm explainability and ethical considerations.
• Updated content on sequential models (LSTMs, GRUs, RNNs) and LLMs.

Maintenance & Community

The project is tied to a published book by Imran Ahmad, Ph.D., a data scientist and visiting professor with expertise in machine learning and cloud platforms (Google Cloud, AWS). Community engagement is facilitated via a Discord server.

Licensing & Compatibility

The repository itself is not explicitly licensed in the README. The book is published by Packt. Compatibility for commercial use or closed-source linking would depend on the book's licensing terms, which are not detailed here.

Limitations & Caveats

The repository primarily serves as supplementary code for a book; it does not represent a standalone, installable library. The depth of coverage for each algorithm is dictated by the book's scope.