AbstractAlgebra.jl is a pure Julia library providing generic abstract algebra structures and algorithms. It serves as the foundational computational algebra layer for the Oscar/Nemocas ecosystem, used by downstream packages Nemo.jl, Hecke.jl, and Singular.jl. The library implements a comprehensive type hierarchy for rings, fields, modules, matrices, polynomials (univariate, multivariate, Laurent, Puiseux, power series), and groups, along with generic algorithms for arithmetic, GCD, factorization, linear algebra (LU, HNF, SNF, Popov forms), Gröbner bases, and more. It is designed for extensibility: any ring implementing the fundamental interface (parent, elem_type, zero, one, +, *, etc.) can use the generic implementations. The codebase is well-tested with conformance tests that verify algebraic axioms for each type, and includes sophisticated infrastructure for attribute caching, map caching, pretty printing, and random element generation. While primarily a library for symbolic computation and research mathematics, it is not a data science or ETL tool.
This repository is a self-paced learning roadmap for algorithmic trading, structured as a hierarchical collection of markdown files. It curates resources, certifications, and project ideas across artificial intelligence, computer science, mathematics, finance, cloud engineering, and software engineering. The repository is entirely documentation-driven; there are no executable applications, data pipelines, or machine learning models. Its primary value lies in its organized curriculum, reusable topic templates, and role-based learning paths (e.g., quant developer, algorithmic trader). While not a software project, it demonstrates high organizational craftsmanship through consistent documentation structure, templates, and CI/CD for link checking and diagram rendering.