Open-source alternatives to Machine Learning Cheat Sheet

This project is a collection of reference materials and educational guides providing theoretical foundations and practical patterns for algorithms, artificial intelligence, and professional technical interviews. It serves as a computer science study guide and a practical reference for solving computational problems through curated notes. The resources provide a learning path for machine learning, covering the mathematical foundations and architectures used to build large language models. It also functions as a technical interview preparation resource, containing common software engineering an

This project is a structured knowledge map and study guide for computer science technical interviews. It serves as a roadmap and reference for core fundamentals, organizing a wide range of technical topics into a categorized guide for developer learning. The knowledge base covers a broad domain of computer science, including data structures, algorithms, and networking protocols. It specifically provides detailed materials for frontend engineering, focusing on JavaScript, browser internals, security, and performance optimization. The project organizes these concepts into a visual knowledge gr

This project is a comprehensive, community-driven directory of machine learning resources, software libraries, and educational materials. It serves as a centralized knowledge base for developers and researchers, organizing tools and frameworks by their primary programming language and technical domain to simplify discovery across the artificial intelligence ecosystem. The collection distinguishes itself by providing a cross-language development index that spans diverse programming environments, including C, C++, Rust, Clojure, and Python. It covers a wide range of specialized capabilities, fr

This repository serves as a structured educational resource for machine learning and data science, providing a centralized collection of tutorials, lecture notes, and implementation guides. It is designed to support self-directed learning by organizing complex technical concepts into a clear, hierarchical path that spans from foundational statistical methods to advanced deep learning architectures. The project distinguishes itself through a comprehensive approach to skill development, bridging the gap between theoretical algorithmic foundations and functional software applications. It offers

This repository serves as a comprehensive educational resource for machine learning, providing a structured collection of lecture notes and reference materials. It covers the fundamental mathematical and statistical principles required to build, evaluate, and optimize predictive models, ranging from basic probability and linear algebra to advanced algorithmic implementations. The content is organized through a hierarchical mapping of concepts that connects mathematical prerequisites to specific machine learning theories. It features a modular design that segments complex topics into discrete,

This project is a website theme for Hugo designed to transform Markdown files into professional academic portfolios, including CVs and publication lists. It functions as a static site template and portfolio builder, enabling the creation of researcher profiles and technical blogs. The framework includes a specialized publication manager that automatically generates individual research pages and citations by importing BibTeX files or DOI references. It also features a dedicated LaTeX mathematics renderer to display technical notation and equations across the site. The system supports a broad

udlbook is a deep learning educational repository and a collection of interactive learning notebooks designed for studying neural network architectures. It serves as a digital repository of formatted mathematical equations and guided examples for learning deep learning concepts. The project provides a mathematical reference for supervised learning and neural network theory using LaTeX rendering. It includes interactive technical documentation and executable notebooks covering gradients, convolutions, and transformers. The system manages educational materials through a file-system based organ

leetcode_101 is a curated library of algorithmic problem sets and a repository of solved LeetCode challenges. It serves as a technical interview guide by providing code implementations for common software engineering interview questions. The project supports a technical interview preparation workflow, focusing on LeetCode problem solving and the study of standardized code solutions for data structures and algorithms. It is designed to facilitate coding skill development and the study of technical interview problems. The repository utilizes markdown-based content authoring and a static-file d

This project is a collection of linear algebra educational notebooks and study resources. It serves as a mathematics study resource providing structured notes and explanations for learning core algebraic concepts. The material is authored as interactive math tutorials and LaTeX mathematical courseware, combining theoretical explanations with executable mathematical examples. Content is delivered through markdown-based study resources and converted into static site mathematics notes for serverless web access. The curriculum covers a range of mathematical theory, including matrix elimination,

This project is an algorithm learning platform and computer science educational resource. It serves as a technical interview study guide, providing structured lessons on data structures and sorting methods. The site is a markdown-based static site that converts technical documentation and algorithmic explanations into static HTML pages. It functions as a system for markdown content publishing to deliver educational material. The platform covers algorithm complexity analysis, problem solving workflows, and general computer science education. It utilizes a component-based UI structure with fil

This repository is a curated collection of technical interview materials designed to assist software engineering candidates in their professional preparation. It functions as a version-controlled knowledge base that organizes common coding challenges and conceptual questions into a structured, navigable format. The project focuses on backend engineering and Java-specific technical assessments, providing a taxonomy of topics that cover core programming concepts and system design principles. By utilizing a hierarchical directory structure and markdown-based documentation, the repository enables

This project is an open-source knowledge repository that serves as a comprehensive technical interview question bank for backend engineering roles. It provides a structured resource for hiring managers and candidates to evaluate proficiency in software design, architectural patterns, and core engineering principles through a curated collection of discussion topics and coding challenges. The repository functions as a programming paradigm evaluation tool, enabling the assessment of a candidate's understanding of object-oriented, functional, and procedural techniques. It distinguishes itself by

This project is a relational database cheat sheet and SQL reference guide. It provides a collection of syntax examples and query documentation for managing relational databases using structured query language. The tool is implemented as a static site with client-side searchable documentation, allowing for immediate filtering of technical content through a browser-based index. The reference covers relational database management, including data retrieval, database schema management, and record maintenance. It also includes guidance on relational data manipulation through table joins and the g

This project serves as a comprehensive, community-driven directory of high-quality open-source Python libraries and tools for machine learning, data science, and artificial intelligence. It functions as a centralized resource for developers to discover, evaluate, and track the maintenance status of software packages across the entire machine learning ecosystem. The platform distinguishes itself through automated popularity tracking and data-driven content curation, which programmatically validate and rank projects based on community activity and development velocity. By organizing these tools

This project is a comprehensive favicon specification guide and browser compatibility matrix. It provides a detailed reference for the image sizes, file formats, and HTML markup required to ensure website icons display correctly across modern and legacy browsers and devices. The resource includes specific technical guides for implementing SVG favicons that use embedded CSS media queries to support system light and dark mode. It also provides a reference for web app manifests and the specific image dimensions needed for installable progressive web applications. The documentation covers broade

This project is an interactive machine learning textbook and educational resource designed to teach the mathematical foundations of artificial intelligence. It functions as a structured course and digital book that covers essential topics ranging from basic arithmetic to advanced calculus, linear algebra, and statistics. The resource utilizes a math visualization library and a collection of interactive code examples to demonstrate abstract principles through algorithmic output. It transforms theoretical study into a practical experience by combining programmable examples with visual guides.

This project is a curated educational resource and technical interview preparation kit. It provides a comprehensive collection of study guides and question banks focused on front-end web development, JavaScript algorithms, and professional coding assessments. The repository includes a technical interview question bank and specialized study sets for JavaScript algorithms. These resources cover conceptual explanations and programming challenges designed to help developers master common coding patterns and theoretical questions. The content covers core web development fundamentals, including HT

This project is a comprehensive guide and reference for PHP best practices and coding standards. It serves as a collection of modern industry guidelines and community-driven patterns designed to help developers write maintainable and efficient code. The resource provides technical documentation and development guidance focused on improving code quality and standardizing PHP application development. To support a global community, the documentation is available in multiple languages. The knowledge base is authored in Markdown and deployed as a static site via pre-rendered HTML files for public

This project is a comprehensive algorithmic interview resource and coding practice repository. It provides a structured curriculum of programming challenges and source code implementations designed to help software engineers master efficient problem-solving techniques and prepare for technical assessments. The repository functions as a curated roadmap, organizing computer science fundamentals by data structure and algorithm topic to facilitate systematic skill development. By moving away from random practice, it supports career advancement training for those seeking to improve their professio

This project is a computer science exam study resource and academic knowledge base. It serves as an exam preparation toolkit providing curated textbooks, past exam papers, and study guides specifically for graduate entrance exams. The repository functions as an algorithm and data structures reference library, containing source code and implementation guides for core computer science fundamentals. It organizes conceptual notes, presentation slides, and mind maps for subjects including operating systems and computer organization. The project is implemented as a markdown-based knowledge base an

This project is a Chinese translation of a comprehensive self-study guide for learning core computer science concepts and theoretical foundations. It serves as a community-driven effort to provide a professional academic path for computer science outside of a formal university program. The project is organized as an open-source translation effort using a pull-request workflow to manage community contributions and peer reviews. Educational materials are maintained as a structured collection of Markdown files and delivered as static site documentation for web access.

This project is a curated collection of technical reference materials and study guides designed for machine learning interview preparation. It provides comprehensive resources for candidates pursuing engineering roles, focusing on deep learning, production infrastructure, and large-scale system design. The repository distinguishes itself through an architecture that combines theoretical research with industrial case studies. It utilizes a pattern-based approach to system design, breaking down complex deployments—such as recommendation engines, search ranking, and ad click prediction—into reus

This project is a comprehensive technical study resource and interview guide for candidates pursuing roles as large language model and AI algorithm engineers. It serves as a structured learning path and technical reference for generative AI, machine learning, and the deployment of models in production environments. The resource provides specialized guides for mastering large language model architectures, diffusion models, and the design of autonomous AI agents. It includes detailed technical references on tool calling, memory management, and multimodal system architectures to assist with tech

This project is a digital technical reference and textbook source focused on graphics programming. It consists of a collection of low-level graphics programming guides provided as Markdown source files designed for digital distribution and study. The project utilizes a Markdown ebook build pipeline to transform source text into HTML5, EPUB3, and Mobi formats. This process leverages Pandoc to convert structured technical documents into standardized digital reading formats through a sequential processing pipeline. The system covers technical document formatting and digital textbook distributio

ML-foundations is a machine learning educational curriculum and computer science study guide. It provides a structured learning path focused on the mathematical foundations and computational prerequisites required for studying machine learning. The project serves as a Python mathematics course, delivering interactive notebooks and coding exercises to teach linear algebra, calculus, and statistics. It translates abstract mathematical formulas into concrete algorithmic code to help learners understand the principles underpinning machine learning algorithms. The curriculum covers data science p

handcalcs is a mathematical documentation generator and Python LaTeX calculation renderer. It serves as an automated calculation sheet tool that converts Python code and numeric calculations into formatted LaTeX mathematical documentation, functioning as both a symbolic math formatter and a Jupyter notebook math extension. The project transforms Python variable names into Greek symbols, subscripts, and standard mathematical notation. It converts code into formatted mathematical expressions that display the original formula, the numeric substitution, and the final result, allowing for the crea

This project is a machine learning coursework repository containing a collection of Python exercises and notebooks. It is designed for implementing foundational machine learning algorithms and completing curriculum assignments through interactive documents that combine instructional text and executable code. The repository provides code formatted for compatibility with automated grading systems, allowing for the submission and validation of technical exercises. It includes predefined environment configurations and dependency locks to ensure consistent execution of data science tools across di