Rust Learning is a GitHub repository or organization with source code, releases, documentation, or project resources.
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High Assurance Rust is a book about developing secure and robust software. It presents a project-based approach to systems programming and low-level software security, teaching Rust by re-implementing a major dynamic collection from its standard library. It discusses using open-source software assurance tools, including rustc, libFuzzer, rr, qemu, differential fuzzing and deductive verification.
rustorka is a non-English web resource for regional media, books, tools, communities, or learning.
Rust native ready-to-use NLP pipelines and transformer-based models (BERT, DistilBERT, GPT2,...).
deeplearn-rs is a Rust library for neural networks and deep learning, described by its author as mostly a proof of concept with a changing API. Implemented models include MNIST handwritten digit recognition and a char-rnn using LSTM, alongside layers such as fully connected, LSTM, softmax, and loss functions, with SGD and RMSProp optimizers. The repository was archived by its owner on Mar 8, 2024, and is read-only.
A GNOME application for learning and prototyping with GNOME technologies, from first tinkering to building and testing a GTK user interface. It includes live GTK/CSS preview, a library of over 100 examples, support for JavaScript, Rust, Python and Vala, declarative UI syntax, autosave, sessions and projects, code diagnostics and terminal output.
burn is a next-generation tensor library and deep learning framework developed by tracel-ai. It is designed to prioritize flexibility, efficiency, and portability, with available resources covering use with Rust, its ecosystem, supported backends, and training and inference functionality.
Candle is a minimalist machine learning framework for Rust with a focus on performance, including GPU support, and ease of use. It provides examples and online browser demos for models such as whisper, LLaMA2, T5, yolo and Segment Anything.
An open source machine learning framework in Rust Δ.
Deep learning in Rust, with shape checked tensors and neural networks.
A free, continuously evolving downloadable book collecting community knowledge on 2D game development. It does not teach a specific tool, instead offering tips and tricks applied to any engine or built from scratch. Editions are available in pseudocode, Python, C++, JavaScript, Lua and Rust; some versions require thorough revision.
A comprehensive toolkit to build Machine Learning applications with Rust.
Bloop is a fast code search engine written in Rust, distributed through GitHub releases. The repository was archived by its owner on Jan 2, 2025, and is now read-only. Release notes for versions v0.6.0 to v0.6.5 list changes such as explaining files in a user-set language, adding multiple files to code studio, code coloring for COBOL, and alternative input types for Chinese users.
GritQL is a declarative query language from Grit for searching and modifying source code. It lets users search with code snippets and metavariables, define custom lints, and apply auto-fix rules, and it supports rewriting JavaScript/TypeScript, Python, JSON, Java, Terraform, Solidity, CSS, Markdown, YAML, Rust, Go and SQL.
m2cgen is a tool that transforms trained machine learning models into native code across a wide range of programming languages including Java, C, Python, Go, JavaScript, C#, R, PHP, Dart, Haskell, Ruby, F#, and Rust, with zero dependencies. Its codebase is hosted in the BayesWitnesses GitHub repository, which includes navigation for installation, development guidance, supported languages, and supported model types.
Notcurses is a C library for building complex textual user interfaces on modern terminal emulators. It does not use Ncurses, though it uses libtinfo from that package, and is not a source-compatible X/Open Curses replacement. Rust, C++, and Python wrappers are available. Source and issue tracking are hosted on GitHub, with a man page API reference.
Open-source runtime for numerical computing that executes MATLAB-syntax code. Built in Rust, it provides a compiler, a virtual machine, and JIT tiers, with a GPU backend powered by wgpu. The project targets CPU and GPU hardware and handles tensor allocations and movement automatically.
A pure Rust tokenizer library that reads tokenizers directly from GGUF model files, requiring no Python, C++ or separate tokenizer files. It supports SPM, BPE, WPM, RWKV and UGM tokenizers tested token-for-token against llama.cpp, and offers batch encoding with optional Rayon parallelism. MIT licensed.
Text Generation Inference is a toolkit for deploying and serving large language models, implemented as a Rust, Python and gRPC server. It supports models including Llama, Falcon, StarCoder, BLOOM and GPT-NeoX, with features such as token streaming, continuous batching and quantization. The repository is archived, read-only, and in maintenance mode, with pull requests limited to minor bug fixes and maintenance.
An open-source resource for learning data structures and algorithms through implementations in various programming languages. The site covers programming languages including Python, Java, JavaScript, Go, Rust, and C++, and organizes algorithms into categories such as sorting, searching, and graph algorithms. It also provides guidance on contributing implementations.