This repository is a collection of solved algorithmic problems and data structure exercises designed for technical interview preparation. It serves as a polyglot reference implementation, providing a set of solved exercises based on a standard textbook to help candidates master the logic and complexity analysis required for coding tests. The project implements the same algorithmic logic across multiple programming languages to demonstrate platform-independent problem solving. This polyglot approach allows for the comparison of implementations across different tech stacks to highlight recurrin
Metalsmith is a Node.js static site generator and static content processor that transforms source files into websites, eBooks, or technical documentation. It functions as a file-to-object transformer, converting directory trees into plain JavaScript objects that can be programmatically manipulated in memory. The project is built around a pluggable build pipeline where files are passed through a sequence of custom functions to transform content and metadata incrementally. This architecture allows users to extend functionality by writing their own plugins or using third-party modules to define
This repository is a structured database of coding interview problems designed to support software engineering career development. It functions as a centralized knowledge base that aggregates technical practice questions, mapping them to specific employer requirements and recurring computer science topics. The project distinguishes itself by clustering interview questions into company-specific collections and labeling them by technical domain. This organization allows users to identify recurring algorithmic patterns and analyze the unique testing styles associated with different organizations
This project is a deep learning study resource and educational curriculum designed for mastering neural network architectures and theory. It serves as a learning platform that combines theoretical notes and mathematical formulas with practical code implementations. The curriculum is centered on the PyTorch framework, providing a structured path for building and training models through annotated code examples and technical reviews of mathematical foundations. The resource utilizes interactive notebooks for executing machine learning algorithms and experimenting with data models. Theoretical
Ce projet est une collection structurée de défis de codage et un guide d'étude pour les entretiens techniques conçus pour aider les développeurs à se préparer aux évaluations en ingénierie logicielle. Il fonctionne comme un index complet de problèmes pratiques, fournissant une feuille de route pour maîtriser les structures de données de base et les concepts algorithmiques par une étude systématique.
Les fonctionnalités principales de fterh/leetcode-curation-topical sont : Technical Interview Preparation, Interview-Focused Problem Sets, Algorithmic Problem Solving, Version-Controlled Knowledge Bases, Data-Driven Content Mapping, Static Site Generators, Coding Interview Preparation, Algorithm Interview Roadmaps.
Les alternatives open-source à fterh/leetcode-curation-topical incluent : careercup/ctci-6th-edition — This repository is a collection of solved algorithmic problems and data structure exercises designed for technical… metalsmith/metalsmith — Metalsmith is a Node.js static site generator and static content processor that transforms source files into websites,… hxu296/leetcode-company-wise-problems-2022 — This repository is a structured database of coding interview problems designed to support software engineering career… mlnlp-world/deeplearning-muli-notes — This project is a deep learning study resource and educational curriculum designed for mastering neural network… hadyang/interview — This project is a comprehensive knowledge base designed to support software engineering interview preparation and… greyireland/algorithm-pattern — This project is an algorithm template library and coding interview study guide providing reusable code patterns for…