Awesome GitHub RepositoriesVisual Style Standardization

ml-visuals is a machine learning figure library and research asset repository containing reusable scientific diagrams and visual templates. It provides a modular system of graphical primitives and layout templates designed to standardize the visual representation of machine learning concepts and architectures. The project utilizes a schema-driven illustration system that defines visual elements and spatial relationships using structured data to ensure reproducible scientific figures. This framework allows for the creation of professional diagrams and charts for academic papers and technical p

SciencePlots is a Matplotlib style library and scientific plotting framework designed to automate the formatting of figures for academic journals and professional scientific publications. It provides a collection of visual presets and configuration rules for academic typography, layout, and resolution. The project features curated color-blind accessible palettes and figure formatters specifically designed to meet the strict submission standards of academic publishers. It includes specialized tools for professional figure styling and the rendering of non-Latin scripts for multilingual support.

This project is a collection of methodological guides and standards for academic document workflows, specifically focusing on a LaTeX scientific writing guide, typesetting standards, and Python data visualization guidelines. It provides a framework for professional scientific paper typesetting and the management of technical documents. The project distinguishes itself by providing specific workflows for programmatic data visualization, including the use of Python and Matlab scripts to ensure high-quality figures and consistent styling. It also details an academic document workflow that integr