Awesome GitHub RepositoriesDynamic Programming

This project is a curated educational resource and solution repository for algorithmic challenges, specifically focused on LeetCode problems. It serves as a technical reference for common data structures and algorithmic patterns, providing verified code implementations across multiple programming languages alongside detailed logic and complexity analysis. The repository functions as a comprehensive study guide for competitive programming and technical interview preparation. It includes specialized learning tools such as an Anki flashcard dataset for spaced repetition and a browser extension t

This project is a comprehensive collection of common computer science algorithms and data structures implemented in Swift. It serves as an educational reference and library for studying computational complexity, algorithmic logic, and data structure engineering through practical code examples. The repository provides a wide suite of data structure implementations, including various types of linked lists, heaps, hash tables, and an extensive range of hierarchical trees such as Red-Black, B-Tree, and Splay trees. It also covers diverse sorting and searching techniques, from basic bubble sort to

This project is a comprehensive, community-maintained knowledge base and toolkit designed for competitive programming. It serves as a centralized repository for algorithmic theory, data structures, and mathematical techniques, providing a structured reference for informatics and collegiate programming competitions. The project distinguishes itself by integrating educational content with a robust suite of automation utilities. It provides a complete workflow for competitive programming, including tools for automated test case generation, solution verification, and direct interaction with onlin

This project is a machine learning algorithm reference and implementation guide that provides theoretical foundations and code for supervised learning, deep learning, and natural language processing. It serves as a comprehensive toolkit for implementing predictive models and a technical reference for algorithm engineering. The project focuses on ensemble learning frameworks, including the construction of decision trees, random forests, and gradient boosting models. It also functions as a probabilistic graphical model library and an NLP algorithm reference, with specific implementations for se

This project is an educational resource designed to teach the mathematical foundations and core algorithms of reinforcement learning. It provides a structured academic curriculum that combines textbooks, lecture materials, and practical code examples to guide learners through the principles of Markov decision processes and reinforcement learning theory. The repository distinguishes itself by integrating a grid-based simulation framework that allows users to test algorithms within custom environments. This environment supports the analysis of agent performance by rendering state values, polici

Portmaster is a host-based network firewall and privacy tool that monitors and controls all system network traffic. It operates by intercepting data packets at the operating system level, allowing it to observe and manage every connection made by local software in real time. The software distinguishes itself through process-aware connection mapping, which correlates active network sockets with specific local applications to provide visibility into data transfers. It utilizes a user-space policy engine to enforce granular security rules, enabling users to restrict internet access, block specif

CrowdSec is a collaborative, distributed security engine designed for threat detection and infrastructure protection. It functions as an intrusion detection system that parses logs and network traffic to identify malicious patterns, utilizing a bucket-based threshold detection model to aggregate events and trigger alerts. The platform is built on a modular architecture that includes a centralized local API server for managing security signals and a relational database for persistent storage of remediation decisions. What distinguishes the project is its decoupled enforcement model, which offl

This project is a reference library of Java implementations for algorithmic coding challenges and data structure patterns. It serves as a study guide for technical interview preparation, providing a curated collection of LeetCode solutions organized by difficulty and algorithmic technique. The collection includes a mapping system that associates specific algorithm problems with the companies that frequently use them in technical interviews. The repository covers a wide range of capability areas, including tree algorithms for hierarchy construction and verification, string processing for sequ

Vowpal Wabbit is an open-source machine learning system designed for online learning, where models update incrementally from streaming data without requiring full retraining. It provides a reduction-based learning framework that composes complex tasks from simpler algorithms, and includes a feature hashing trick that maps unbounded feature names into a fixed-size vector space to keep memory usage constant regardless of dataset size. The system supports distributed training across a cluster using an allreduce protocol for synchronized updates, and offers an active learning query strategy that s

This project is a collection of reference implementations for algorithms, mathematics, cryptography, compression, and machine learning written in C#. It serves as an educational library providing standard implementations of sorting, searching, and graph theory algorithms. The repository covers a wide range of computational domains, including combinatorial optimization for constraint satisfaction and scheduling, as well as symmetric and classical cryptographic ciphers. It also provides reference code for lossless data compression techniques and fundamental machine learning primitives such as r

Penrose is a compiler that transforms structured mathematical notation into optimized SVG diagrams. It uses a three-stage pipeline of separate domain, substance, and style files to define mathematical objects, relationships, and visual presentation, then solves continuous optimization problems with user-defined spatial constraints and objectives to automatically arrange diagram elements. The system separates diagram content from visual style using distinct declarative languages, and provides a typed domain language with subtype hierarchies for mathematical objects. It supports embedding compi

LogicStack-LeetCode is a curated repository of solved algorithm problems and data structure implementations, primarily drawn from the LeetCode platform. Its core identity is a structured collection of solutions designed to support technical interview preparation and competitive programming practice, with each solution accompanied by complexity analyses to help engineers understand performance trade-offs. The repository distinguishes itself through its breadth of coverage across fundamental algorithmic patterns and data structures. It includes implementations for array manipulation, string pro

CVXPY is a Python-embedded domain-specific language for modeling and solving convex optimization problems using natural mathematical syntax. It is built on a disciplined convex programming framework that automatically enforces convexity rules, ensuring that problems formulated by the user are valid for convex solvers. The project also functions as a multi-solver optimization interface, abstracting away backend details and dispatching problems to specialized solvers like ECOS, SCS, and Gurobi without manual configuration. Beyond standard convex optimization, CVXPY extends its reach to geometri

هذا المشروع عبارة عن مجموعة شاملة من مكتبات وأدوات C++ توفر تطبيقات مرجعية لهياكل البيانات، وخوارزميات الرسوم البيانية، والمنطق الثنائي (bitwise logic). يعمل كمرجع لخوارزميات C++ يحتوي على أكثر من 180 مسألة برمجية محلولة ومجموعة أدوات متخصصة للبرمجة التنافسية. يتميز المستودع بمكتبات واسعة النطاق لمعالجة البتات منخفضة المستوى لفحوصات التكافؤ، واكتشاف ترتيب البايتات (endianness)، والمنطق القائم على XOR. كما يوفر مجموعة واسعة من الحلول المرجعية للتحديات الخوارزمية المعقدة التي تتضمن التراجع (backtracking)، ونظرية الرسوم البيانية، والبرمجة الديناميكية. تغطي مساحة القدرات منظمات البيانات الخطية والهرمية الأساسية، بما في ذلك القوائم المرتبطة، والمكدسات، والطوابير، وأشجار البحث الثنائية. يتضمن مجموعة كاملة من خوارزميات الرسوم البيانية للبحث عن المسارات والأشجار الممتدة، وطرق متنوعة للفرز والبحث، وتحويلات المصفوفات، وأدوات معالجة النصوص. بالإضافة إلى ذلك، يغطي الدوال الحسابية الرياضية، وضغط البيانات بدون فقدان، وشفرات التشفير الأساسية.

PyPortfolioOpt is a comprehensive portfolio optimization library for Python that provides a full suite of methods for constructing and analyzing investment portfolios. At its core, the library implements mean-variance optimization, the Black-Litterman Bayesian model, and Hierarchical Risk Parity, giving users multiple approaches to asset allocation. It includes a complete covariance estimation toolkit with interchangeable estimators such as sample, exponential, shrinkage, and minimum-covariance-determinant methods, along with expected return estimation using historical mean, exponential weight

توفر هذه المكتبة إطار عمل لتعريف آلات الحالة المحدودة (finite state machines) داخل فئات Ruby لإدارة دورات حياة الكائنات المعقدة. تعمل كمحرك سير عمل تصريحي، مما يسمح للمطورين بنمذجة حالات الكائنات، والأحداث، والانتقالات من خلال لغة خاصة بالمجال (DSL) سهلة القراءة. من خلال التكامل المباشر مع طبقات استمرارية قاعدة البيانات، يضمن إطار العمل مزامنة تغييرات الحالة مع سجلات التخزين مع الحفاظ على سلامة البيانات من خلال إدارة المعاملات وقفل الصفوف. تتميز المكتبة بفرض قواعد عمل صارمة من خلال حراس الانتقال المشروط ومنع التعديل المباشر للحالة، مما يضمن حدوث جميع تغييرات دورة الحياة حصرياً من خلال أحداث محددة. وهي تدعم آلات حالة متعددة ومستقلة داخل فئة واحدة عن طريق تعيينها لحقول قاعدة بيانات متميزة، مما يوفر تحكماً معزولاً في دورة الحياة. علاوة على ذلك، تقوم تلقائياً بإنشاء طرق مثيل ديناميكية للاستعلام عن الحالات وتشغيل الأحداث، إلى جانب نطاقات استعلام قاعدة البيانات التي تبسط تصفية الكائنات بناءً على حالتها الحالية. بعيداً عن إدارة دورة الحياة الأساسية، تتضمن المكتبة أدوات لتعريب أسماء الحالات لدعم الواجهات متعددة اللغات وتوفر خطافات (hooks) لتنفيذ منطق مخصص قبل أو بعد الانتقالات. كما تقدم أدوات مطابقة اختبار متخصصة للتحقق من تكوينات آلة الحالة ومنطق الانتقال داخل مجموعات الاختبار الآلية. يتضمن المشروع أدوات لتجميع الكود المصدري والتكوينات في توثيق منظم للمساعدة في مرجع النظام.

LeetCode-Swift is a collection of algorithm solutions written in Swift, designed for coding interview preparation. Each solution is implemented as a self-contained function with no external dependencies, making it easy to run and test. The repository organizes solutions by topic and company, and every file includes time and space complexity annotations, allowing quick evaluation of algorithmic efficiency. What sets this repository apart is its flat file structure and the way solutions are tagged with the companies that asked them in interviews, enabling targeted practice. All code resides in

هذا المشروع عبارة عن مكتبة آلات ناقلات الدعم (SVM) تم تنفيذها بلغة C، وتوفر محركاً لمهام التصنيف والانحدار. تعمل كمكتبة نواة لتعلم الآلة ومصحح نماذج إحصائية يُستخدم لتصنيف نقاط البيانات والتنبؤ بالقيم الرقمية المستمرة. تسمح المكتبة بتعريف وظائف نواة مخصصة لحساب التشابه بين نقاط البيانات في مجموعات بيانات متخصصة. كما تتضمن أدوات للنمذجة الاحتمالية، مثل تقدير عضوية الفئة، وكثافة البيانات، وحدود التوزيع. تغطي القدرات الواسعة تدريب النماذج لمجموعات البيانات متعددة الفئات، بما في ذلك إدارة البيانات غير المتوازنة من خلال وظائف الخسارة المرجحة. يوفر النظام سير عمل لاختيار المعلمات الفائقة وتحسين النموذج باستخدام خطوط دقة الكنتور والتحقق المتبادل الطبقي. تتضمن أدوات معالجة البيانات المسبقة للتحقق من المدخلات وتحجيم السمات لتطبيع مقادير الميزات.

This repository is a curated guide and implementation library of coding patterns used to solve data structures and algorithms problems. It serves as a technical interview study resource, providing a comprehensive set of strategies and computational logic examples for optimizing time and space complexity. The project focuses on standardized algorithmic patterns, including sliding windows, two pointers, and dynamic programming. It features specific implementations for a wide range of challenges, such as LeetCode problem solutions and specialized techniques like cyclic sort and bitwise XOR opera

This project is a data mining algorithm library and machine learning reference implementation. It provides a collection of tools for performing classification, clustering, and association rule mining, as well as a toolkit for nature-inspired optimization. The library includes specialized utilities for graph and sequence mining, enabling the extraction of frequent subgraphs and sequential patterns. It also features a dimensionality reduction utility that uses rough set theory to remove redundant attributes from datasets. The project covers a broad range of analytical capabilities, including n