Projects sharing features with PlotNeuralNet

Typst is a programmable, markup-based typesetting engine designed for professional document creation. It functions as a scriptable publishing toolchain that transforms plain text and code into complex, paginated outputs. By utilizing a high-performance compiler, the system automates document assembly, mathematical rendering, and dynamic content generation, providing a unified workflow for academic and technical authoring. The engine distinguishes itself through a declarative layout framework that uses cascading rules to manage document structure and visual styling. Unlike traditional systems,

Awesome-Backbones is a modular deep learning framework designed for the end-to-end lifecycle of computer vision models. It provides an integrated platform for training, benchmarking, and deploying convolutional and transformer-based neural network architectures for image classification tasks. The framework distinguishes itself through a configuration-driven approach to model assembly, allowing users to define backbone, neck, and head components externally. It includes a specialized toolkit for model interpretability, utilizing gradient-based visualization techniques to generate class activati

This project is an educational platform designed to teach artificial intelligence, neural networks, and data science through a combination of structured textbooks and interactive learning resources. It provides a comprehensive curriculum that guides students through sequential learning paths, bridging the gap between mathematical theory and practical software implementation. The platform distinguishes itself by integrating executable code environments and dynamic browser-based visualizations directly into its educational content. These tools allow users to modify model implementations in real

This project is a curated directory of resources, libraries, and frameworks designed to support the development, training, and deployment of neural network models. It serves as a comprehensive guide for navigating the machine learning ecosystem, providing structured access to software utilities and research materials. The directory distinguishes itself by aggregating tools across the entire machine learning lifecycle, ranging from data management and experiment tracking to production-ready model deployment. It functions as a central hub for discovering both foundational academic research and

This project is a declarative visualization library and geospatial framework designed for rendering large-scale data sets within web browsers. It functions as a high-performance graphics engine that leverages hardware acceleration to display complex 2D and 3D visual layers, enabling the visualization of millions of data points through a structured, component-based syntax. The framework distinguishes itself through its ability to synchronize custom data visualizations with third-party mapping platforms. By managing camera states and coordinate systems, it allows developers to overlay high-perf

ggpy is a Python library for statistical data visualization based on the grammar of graphics. It functions as a declarative framework for building complex charts by mapping data variables to visual properties through a structured coordinate system. The library enables the construction of composite visualizations by layering geometric shapes and statistical summaries. It utilizes a system of continuous and discrete scales to translate raw data into visual attributes and supports facet-based plotting to segment a single visualization into a grid of subplots based on variable categories. Visual

This project is an open source discovery resource that provides curated lists of reusable code and libraries to help developers find technical solutions for specific tasks. It utilizes a category-based indexing system to organize diverse software tools by their functional capabilities. The repository is structured as a collection of markdown-based documentation and static content, serving as a directory for manual discovery and reference. The directory covers a wide range of capability areas, including cross-platform application development, cybersecurity tool creation, network protocol impl

This project is a browser-based machine learning education tool and neural network sandbox. It provides an interactive environment for experimenting with network architectures and hyperparameters to understand deep learning concepts. The tool functions as a visualizer for TensorFlow neural networks, allowing users to see how models learn and classify data in real time. It enables the prototyping of model architectures to observe how different hidden layers and neurons affect a network's ability to solve specific data patterns. The system covers neural network architecture and operation visua

This is a curated collection of resources designed for self-directed study in programming language theory. It functions as a structured reading list and bibliography covering major topics including semantics, type systems, module systems, and recursion schemes. Each major subtopic—such as module systems and recursion schemes—has its own dedicated directory of carefully selected papers, talks, and articles. The collection is hand-picked by the curator to ensure relevance and quality. Resources are organized by subtopic into separate markdown files, and the entire repository is version-controll

c3 is a charting library for creating reusable data visualizations and interactive charts based on the D3 JavaScript framework. It functions as a declarative visualization framework that generates complex charts through high-level configurations rather than manual SVG manipulation. The project provides a reusable chart component library and a tool for converting raw datasets into scalable vector graphics. These capabilities allow for the implementation of interactive data visualizations and web-based data reporting using standardized templates. The library supports the development of custom

metrics-graphics is a data visualization library and declarative graphics framework designed to create principled data graphics and layouts. It functions as a statistical graphics engine that maps raw data to geometric shapes and structured objects to render complex, data-driven layouts. The toolkit specializes in rendering time-series data through line charts and scatterplots using a consistent layout system. It also provides capabilities for statistical distribution mapping, including the creation of rug plots to represent one-dimensional data density. The system covers a broad surface of

RenderCV is a command-line utility designed to transform structured YAML data into professionally typeset documents. By separating content from presentation, it allows users to maintain version-controlled resumes that are automatically rendered into high-quality PDF, HTML, and Markdown formats. The system leverages a specialized typesetting engine to ensure precise layout control and professional-grade typography. The project distinguishes itself through a schema-driven approach that enforces strict data validation, ensuring that input files are error-free before processing. Users can customi

PDFMathTranslate is a document translation tool designed to convert technical and scientific files into multiple languages while preserving their original visual layout. It functions as a specialized processor for academic research papers, ensuring that complex mathematical notation and technical formatting remain intact throughout the translation process. The system utilizes a layout-preserving parsing engine that extracts text and structural metadata while maintaining the spatial coordinates of every document element. To handle the translation of technical content, it employs an intermediat

This project is a document generation tool designed to create professional resumes and academic curriculum vitae using the LaTeX typesetting system. It provides a structured framework that separates raw career data from visual formatting, allowing users to compile structured source files into high-quality PDF documents. The system utilizes a template-driven layout engine and macro-based typesetting to enforce consistent visual constraints and typography. By isolating content from styling, it ensures that career histories, skills, and education are presented in a clean, standardized format sui

This project serves as a comprehensive textbook and educational resource for data analysis using the Python ecosystem. It provides a structured guide to manipulating, cleaning, and processing datasets, focusing on the core tools required for numerical computing and statistical analysis. The repository distinguishes itself by offering a collection of practical code examples and workflows that demonstrate how to perform complex data tasks. It covers the application of vectorized numerical computations, the management of time-indexed data, and the creation of statistical visualizations to commun

MNN is a high-performance inference engine and framework designed for on-device machine learning. It provides a comprehensive environment for executing, optimizing, and deploying neural network models directly on mobile and resource-constrained edge devices. The framework distinguishes itself through a robust model optimization toolkit that supports quantization, compression, and structural graph manipulation to minimize memory footprint and maximize execution speed. It features a modular architecture that abstracts hardware-specific backends, allowing models to run efficiently across diverse

This project is a curated resource directory and tooling list for the extended Berkeley Packet Filter technology. It serves as a reference guide to software projects, libraries, and frameworks built on the eBPF kernel subsystem. The directory covers a range of domains including Linux kernel observability, system security monitoring, and cloud native networking. It also provides an eBPF learning path with tutorials and guides for those implementing custom kernel instrumentation. The collection is maintained as a markdown-based directory using a manual curation workflow to organize external to

This project is an educational resource providing a mathematical foundation in probability and statistics for machine learning. It offers a collection of interactive notebooks and textbooks designed to explain core statistical theories and data science principles through practical code examples. The content is structured into modular chapters that allow for self-paced learning of topics such as Bayesian inference and probability distributions. By utilizing browser-based execution and declarative visualization, the project enables users to manipulate variables and observe mathematical outcomes

This project is a digital book directory and academic literature library. It serves as a curated collection of multidisciplinary texts and research materials organized by subject and publication year. The system uses a subject-based content catalog to arrange electronic books into specific domains. It employs visual markers and symbol-based encoding to distinguish between free and paid content. The directory provides capabilities for technical literature discovery and academic reading list management. Users can browse materials by subject and filter titles by recency using publication dates.

react-docgen is a static analysis library and automated documentation tool designed to extract structured metadata from React component definitions. It functions as an AST-based code parser that transforms source code into machine-readable formats, enabling the programmatic generation of technical documentation and developer portals. The tool identifies component names, descriptions, and methods by analyzing source code without executing it. It specifically extracts detailed property information, including type definitions, default values, and human-readable descriptions derived from docblock

Doxygen is a source code documentation generator and multi-language API reference tool. It extracts annotated comments from source code to create structured technical manuals and searchable software libraries in formats including HTML, LaTeX, and PDF. The project functions as a static code analysis visualizer, generating call graphs, class diagrams, and inheritance hierarchies to illustrate codebase structure. It also serves as an XML documentation export engine, producing structured metadata that can be transformed via XSLT or third-party tools. Beyond API extraction, the tool provides a Ma

Terminal-based presentations using Pandoc

Buku is a personal bookmark manager that provides a command line interface, a portable bookmark database, and a self-hosted server for organizing web links. It functions as a command line knowledge base for saving, tagging, and searching web resources. The system features a portable, mergeable database that supports AES-256 encryption and is designed for cross-device data synchronization. It includes a RESTful API and a self-hosted web interface, allowing users to manage their collection via a browser or programmatic requests. Capabilities include automatic metadata fetching to populate page

Freely-licensed LibreOffice Impress templates

OCRmyPDF is a tool for converting image-based PDF files into machine-readable documents by adding a searchable text layer via optical character recognition. It functions as a multi-language processor capable of detecting and extracting text in over 100 different languages using linguistic data packs. The software includes a PDF image optimizer to remove image artifacts and correct page skew to improve recognition accuracy. It also provides a converter to transform scanned documents into the PDF/A standard for long-term digital archiving. The system manages PDF optimization by compressing emb

Generate HTML5 slideshows from markdown, ReST, or textile