Open-source alternatives to Book3 Elements Of Mathematics

This project is a Portuguese translation of a comprehensive JavaScript programming guide and educational resource. It serves as a technical textbook designed to make JavaScript education accessible to Portuguese speakers, covering fundamental syntax, data structures, and programming logic. The material provides instruction on both web development and server-side application building. It includes a structured approach to learning how to manipulate the browser document model and handle user events to create interactive user interfaces. The resource is delivered through multiple formats, includ

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

This project is an educational resource focused on machine learning mathematics education. It provides a curriculum for the mathematical foundations required to understand and implement machine learning algorithms, covering linear algebra, calculus, probability, and optimization. The resource includes structured mathematics modules and a foundation curriculum paired with practice exercises, instructor manuals, and solution guides. It offers technical textbook supplementation through downloadable PDF materials and supplementary learning content such as video lectures and presentation slides.

This project is a machine learning study guide and technical knowledge base. It serves as a version-controlled repository of mathematical formulas and algorithmic explanations, providing instructional material and reference notes for the study of artificial intelligence. The content is structured as a markdown-based knowledge base that pairs theoretical mathematical explanations directly with code implementations. This approach demonstrates model mechanics in practice across several specialized domains, including deep learning research, probabilistic graphical modeling, and reinforcement lear

This project is a technical curriculum and learning path for machine learning, providing a structured sequence of mathematical foundations, core concepts, and professional workflows. It serves as a comprehensive guide and resource index that connects theoretical principles to the specific software libraries and tools used in real-world implementation. The repository functions as a project workflow blueprint, outlining the sequential steps required to solve machine learning problems from initial discovery through to final deployment. It maps theoretical mathematical principles to practical app

This repository is a collection of machine learning theory notes and mathematical references. It serves as a structured study guide containing conceptual explanations and handwritten mathematical derivations of the foundations and core formulas used in the field. The content focuses on the mathematical derivation of algorithms, breaking down the step-by-step logic and proofs required to understand their inner workings. These academic records utilize typesetting for precise scientific notation and mathematical documentation. The materials are organized as a markdown-based study guide with a t

This project is a comprehensive set of educational resources and structured curricula for learning artificial intelligence and deep learning. It provides a machine learning curriculum consisting of lecture materials and interactive notebooks centered on implementing models using the PyTorch framework. The instructional design follows a code-first approach, where students implement working models before studying the underlying theoretical mathematics. The curriculum is delivered via executable documents that combine live code, equations, and narrative text to guide the implementation and deplo

This project is a Python machine learning education kit that provides curated datasets and visualization scripts to teach fundamental machine learning concepts. It functions as both a machine learning visualization library and a collection of educational datasets designed for demonstrating and testing common models and patterns. The toolkit focuses on illustrating the internal logic and operational patterns of machine learning algorithms. It generates figures and datasets that visualize how different models behave and operate on data to aid in the learning process. The implementation utilize

This project is an open educational curriculum designed to teach the fundamental concepts and practical applications of artificial intelligence. It provides a structured, modular path for developers to build technical proficiency in machine learning, neural networks, computer vision, and natural language processing. The curriculum distinguishes itself through an interactive learning path that integrates executable code blocks directly into the documentation. By utilizing a series of Jupyter notebooks, learners can run experiments, visualize results, and complete hands-on coding exercises with

This project is an open-source, interactive educational platform designed to teach deep learning through a comprehensive, code-first curriculum. It provides a structured learning path that covers foundational mathematics, modern neural network architectures, and practical optimization techniques, enabling practitioners to master complex artificial intelligence concepts through hands-on experimentation. The platform distinguishes itself by integrating technical explanations with executable Jupyter notebooks. This design allows readers to modify code and hyperparameters in real-time, facilitati

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,

LLM101n is an educational machine learning curriculum and open-source resource designed to teach the fundamental principles and practical implementation of large language models. It functions as a technical manual that guides users through the end-to-end process of building and training neural network architectures from scratch using a dynamic tensor library for automatic differentiation and GPU-accelerated computation. The project distinguishes itself through interactive, notebook-based instruction that allows for real-time visualization of training processes. It supports rapid experimentati

Learn-SQL is an interactive platform and exercise repository designed for beginner programming education, specifically focusing on SQL query practice and relational database management. It functions as an in-browser learning tool where users can execute database scripts and practice foundational querying skills without requiring any backend server infrastructure. The platform evaluates database queries directly inside the browser session by compiling an entire SQL engine into portable WebAssembly bytecode. Curriculum content, lesson instructions, and challenge prompts are stored as plain text

This project is a comprehensive educational curriculum and engineering handbook focused on the lifecycle of large language models. It serves as a structured knowledge base for machine learning practitioners, covering the fundamental mathematical and architectural principles of transformer-based sequence modeling, as well as the practical implementation of supervised instruction fine-tuning and preference-based model alignment. The repository distinguishes itself by providing a deep dive into advanced model composition and optimization techniques. It details methodologies for weight-space mode

One Small Step is an educational resource that explains core AI and large language model concepts through short, accessible articles designed to be read in under five minutes. It covers the structure and function of key LLM components like attention mechanisms and tokenization, as well as foundational machine learning mathematics such as matrix rank and overfitting. The project also serves as a guide to the GGUF file format, which packages all model parameters and metadata into a single compact binary file for cross-platform deployment without external dependencies. It explains how this forma

NexT is a responsive, elegant static blog theme for Hexo that generates HTML pages from Markdown posts. It is designed as a pre-built visual design for the Hexo framework, producing mobile-friendly layouts that adapt across devices with support for dark mode and multiple visual schemes. The theme distinguishes itself through extensive customization options, including five built-in code highlighting themes for technical blog posts and a multilingual interface supporting over 15 languages. It offers configuration flexibility by allowing theme settings to be stored either in the main Hexo config

This project is a responsive Jekyll blog theme and static site template designed as a technical blogging framework. It converts markdown content into a professional personal blog with integrated support for social profile management. The template is configured as a progressive web app, providing offline access and an app-like experience for visitors. It specifically caters to technical documentation by supporting the rendering of mathematical notation, formatted code snippets, and embedded presentations. The site includes capabilities for reader engagement through discussion system integrati

al-folio is a Jekyll academic theme and portfolio generator designed for researchers and professors to build professional homepages, lab sites, and research profiles. It functions as a system for creating a digital academic identity, combining a website template with tools for scientific and academic publishing. The project distinguishes itself through specialized scholarly workflows, such as automated publication lists and bibliography management driven by BibTeX files. It provides specific layouts for digital academic CVs, research portfolios, and the rendering of mathematical expressions a

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

interviews.ai is a technical study resource and educational book designed for machine learning engineering roles. It serves as a comprehensive guide for mastering theoretical and practical fundamentals, specifically providing a collection of solved interview questions and answers focused on artificial intelligence and deep learning. The project covers core AI curriculum including information theory, Bayesian statistics, and neural network architectures. It provides instructional content and solved technical exercises to assist with deep learning interview preparation and machine learning exam

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,

Roadmap-Docs is a technical career roadmap repository that provides structured learning paths for software engineering, data science, and artificial intelligence roles. It functions as a professional development curriculum, mapping essential technical milestones and industry-standard tools to guide career advancement. The platform integrates a job market trend analyzer that evaluates industry job postings to identify high-demand skills and competencies. By utilizing an automated data pipeline, the system updates these educational roadmaps to reflect real-time industry requirements and evolvin

This project is an open-source educational curriculum designed to provide a structured path for developers to master machine learning and generative AI. It functions as a technical skill development platform, offering comprehensive study materials that guide learners through fundamental concepts, algorithms, and the practical implementation of artificial intelligence models from scratch. The curriculum distinguishes itself through a pedagogy centered on interactive Jupyter Notebooks, which allow students to execute code cells directly within narrative documents for immediate visual feedback.

This project is a machine learning reference guide and condensed cheat sheet providing a curated collection of classical equations, diagrams, and core concepts. It serves as a technical interview study guide focused on the mathematical foundations and theoretical principles required for machine learning engineering roles. The resource facilitates the review of algorithm theory and data science interview preparation by offering a centralized location to recall fundamental machine learning patterns and mathematical proofs. It functions as a study guide for academic exams and a quick-reference t

This project is a web development tutorial site and a Ruby on Rails learning resource designed as a beginner programming guide. It serves as a technical workshop curriculum and a structured framework for organizing and coaching community-led programming events. The site functions as a static site generator that converts Markdown content and templates into pre-rendered HTML pages. This architecture supports the delivery of step-by-step guides and instructional materials used to teach new learners how to build web applications. The content covers a broad range of capabilities, including Ruby o

Jekyll Now is a starter kit and static site template designed for the rapid deployment of blogs. It provides a pre-configured foundation that integrates a GitHub Pages theme to enable website hosting without the use of command line tools. The project features a web-based content manager that allows users to update blog posts and site metadata by editing files directly within a browser. This no-code management workflow is paired with a responsive design intended for personal brand websites, including social media integration and biography sections. The framework covers static site generation

Astro Paper is a minimal and accessible blog theme for the Astro framework, designed to create SEO-optimized static websites. It serves as a pre-configured template for building personal blogs and technical portfolios that render content from Markdown and MDX files. The project distinguishes itself through specialized support for technical writing, including LaTeX mathematical equation rendering and code syntax highlighting. It also automates social media presence via the build-time generation of dynamic Open Graph images and social metadata. The framework covers a broad range of site manage