Rust для машинного обучения - библиотека: различия между версиями
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* [https://github.com/selforgmap/som-rust selforgmap/som-rust - Self Organizing Map (SOM) is a type of Artificial Neural Network (ANN) that is trained using an unsupervised, competitive learning to produce a low dimensional, discretized representation (feature map) of higher dimensional data.]<br> | * [https://github.com/selforgmap/som-rust selforgmap/som-rust - Self Organizing Map (SOM) is a type of Artificial Neural Network (ANN) that is trained using an unsupervised, competitive learning to produce a low dimensional, discretized representation (feature map) of higher dimensional data.]<br> | ||
== | ==СТАТИСТИЧЕСКИЕ МОДЕЛИ== | ||
Redpoll/changepoint - Includes the following change point detection algorithms: Bocpd -- Online Bayesian Change Point Detection Reference. BocpdTruncated -- Same as Bocpd but truncated the run-length distribution when those lengths are unlikely. | * [https://gitlab.com/Redpoll/changepoint Redpoll/changepoint - Includes the following change point detection algorithms: Bocpd -- Online Bayesian Change Point Detection Reference. BocpdTruncated -- Same as Bocpd but truncated the run-length distribution when those lengths are unlikely.]<br> | ||
krfricke/arima - ARIMA modelling for Rust | * [https://github.com/krfricke/arima krfricke/arima - ARIMA modelling for Rust]<br> | ||
Daingun/automatica - Automatic Control Systems Library | * [https://gitlab.com/daingun/automatica Daingun/automatica - Automatic Control Systems Library]<br> | ||
rbagd/rust-linearkalman - Kalman filtering and smoothing in Rust | * [https://github.com/rbagd/rust-linearkalman rbagd/rust-linearkalman - Kalman filtering and smoothing in Rust]<br> | ||
sanity/pair_adjacent_violators - An implementation of the Pair Adjacent Violators algorithm for isotonic regression in Rust | * [https://github.com/sanity/pair_adjacent_violators sanity/pair_adjacent_violators - An implementation of the Pair Adjacent Violators algorithm for isotonic regression in Rust]<br> | ||
== | ==ЭВОЛЮЦИОННЫЕ АЛГОРИТМЫ== | ||
martinus/differential-evolution-rs - Generic Differential Evolution for Rust | * [https://github.com/martinus/differential-evolution-rs martinus/differential-evolution-rs - Generic Differential Evolution for Rust]<br> | ||
innoave/genevo - Execute genetic algorithm (GA) simulations in a customizable and extensible way. | * [https://github.com/innoave/genevo innoave/genevo - Execute genetic algorithm (GA) simulations in a customizable and extensible way.]<br> | ||
Jeffail/spiril - Rust library for genetic algorithms | * [https://github.com/Jeffail/spiril Jeffail/spiril - Rust library for genetic algorithms]<br> | ||
sotrh/rust-genetic-algorithm - Example of a genetic algorithm in Rust and Python | * [https://github.com/sotrh/rust-genetic-algorithm sotrh/rust-genetic-algorithm - Example of a genetic algorithm in Rust and Python]<br> | ||
willi-kappler/darwin-rs - darwin-rs, evolutionary algorithms with | * [https://github.com/willi-kappler/darwin-rs willi-kappler/darwin-rs - darwin-rs, evolutionary algorithms with Rust]<br> | ||
== | ==ДРУГИЕ ПРОЕКТЫ== | ||
Are we learning yet?, A work-in-progress to catalog the state of machine learning in Rust | * [http://www.arewelearningyet.com/ Are we learning yet?, A work-in-progress to catalog the state of machine learning in Rust]<br> | ||
e-tony/best-of-ml-rust, A ranked list of awesome machine learning Rust libraries | * [https://github.com/e-tony/best-of-ml-rust e-tony/best-of-ml-rust, A ranked list of awesome machine learning Rust libraries]<br> | ||
The Best 51 Rust Machine learning Libraries, RustRepo | * [https://rustrepo.com/catalog/rust-machine-learning_newest_1 The Best 51 Rust Machine learning Libraries, RustRepo]<br> | ||
rust-unofficial/awesome-rust, A curated list of Rust code and resources | * [https://github.com/rust-unofficial/awesome-rust rust-unofficial/awesome-rust, A curated list of Rust code and resources]<br> | ||
Top 16 Rust Machine learning Projects, Open-source Rust projects categorized as Machine learning | * [https://www.libhunt.com/l/rust/t/machine-learning Top 16 Rust Machine learning Projects, Open-source Rust projects categorized as Machine learning]<br> | ||
39+ Best Rust Machine learning frameworks, libraries, software and resourcese, ReposHub | * [https://reposhub.com/rust/machine-learning 39+ Best Rust Machine learning frameworks, libraries, software and resourcese, ReposHub]<br> | ||
== | ==БЛОГИ== | ||
About Rust’s Machine Learning Community, Medium, 2016/1/6, Autumn Engineering | * [https://medium.com/@autumn_eng/about-rust-s-machine-learning-community-4cda5ec8a790#.hvkp56j3f About Rust’s Machine Learning Community, Medium, 2016/1/6, Autumn Engineering]<br> | ||
Rust vs Python: Technology And Business Comparison, 2021/3/4, Miłosz Kaczorowski | * [https://www.ideamotive.co/blog/rust-vs-python-technology-and-business-comparison Rust vs Python: Technology And Business Comparison, 2021/3/4, Miłosz Kaczorowski]<br> | ||
I wrote one of the fastest DataFrame libraries, 2021/2/28, Ritchie Vink | * [https://www.ritchievink.com/blog/2021/02/28/i-wrote-one-of-the-fastest-dataframe-libraries I wrote one of the fastest DataFrame libraries, 2021/2/28, Ritchie Vink]<br> | ||
Polars: The fastest DataFrame library you've never heard of 2021/1/19, Analytics Vidhya | * [https://www.analyticsvidhya.com/blog/2021/06/polars-the-fastest-dataframe-library-youve-never-heard-of Polars: The fastest DataFrame library you've never heard of 2021/1/19, Analytics Vidhya]<br> | ||
Data Manipulation: Polars vs Rust, 2021/3/13, Xavier Tao | * [https://able.bio/haixuanTao/data-manipulation-polars-vs-rust--3def44c8 Data Manipulation: Polars vs Rust, 2021/3/13, Xavier Tao]<br> | ||
State of Machine Learning in Rust – Ehsan's Blog, 2019/5/13, Published by Ehsan | * [https://ehsanmkermani.com/2019/05/13/state-of-machine-learning-in-rust/ State of Machine Learning in Rust – Ehsan's Blog, 2019/5/13, Published by Ehsan]<br> | ||
Ritchie Vink, Machine Learning Engineer, writes Polars, one of the fastest DataFrame libraries in Python and Rust, Xomnia, 2021/5/11 | * [https://www.xomnia.com/post/ritchie-vink-writes-polars-one-of-the-fastest-dataframe-libraries-in-python-and-rust/ Ritchie Vink, Machine Learning Engineer, writes Polars, one of the fastest DataFrame libraries in Python and Rust, Xomnia, 2021/5/11]<br> | ||
Quickwit: A highly cost-efficient search engine in Rust, 2021/7/13, quickwit, PAUL MASUREL | * [https://quickwit.io/blog/quickwit-first-release/ Quickwit: A highly cost-efficient search engine in Rust, 2021/7/13, quickwit, PAUL MASUREL]<br> | ||
* [https://serokell.io/blog/rust-in-production-qovery Check out Rust in Production, 2021/8/10, Qovery, @serokell]<br> | |||
Check out Rust in Production, 2021/8/10, Qovery, @serokell | * [https://medium.com/geekculture/why-i-started-rust-instead-of-stick-to-python-626bab07479a Why I started Rust instead of stick to Python, 2021/9/26, Medium, Geek Culture, Marshal SHI]<br> | ||
Why I started Rust instead of stick to Python, 2021/9/26, Medium, Geek Culture, Marshal SHI | |||
== | ==ОБУЧЕНИЕ== | ||
Rust Machine Learning Book, Examples of KMeans and DBSCAN with linfa-clustering | * [https://rust-ml.github.io/book/chapter_1.html Rust Machine Learning Book, Examples of KMeans and DBSCAN with linfa-clustering]<br> | ||
Artificial Intelligence and Machine Learning – Practical Rust Projects | * [http://devguis.com/6-artificial-intelligence-and-machine-learning-practical-rust-projects-building-game-physical-computing-and-machine-learning-applications.html Artificial Intelligence and Machine Learning – Practical Rust Projects(Building Game, Physical Computing) – Dev Guis , 2021/5/19]<br> | ||
Machine learning in Rust using Linfa, LogRocket Blog, 2021/4/30, Timeular, Mario Zupan, Examples of LogisticRegression | * [https://blog.logrocket.com/machine-learning-in-rust-using-linfa/ Machine learning in Rust using Linfa, LogRocket Blog, 2021/4/30, Timeular, Mario Zupan, Examples of LogisticRegression]<br> | ||
Machine Learning in Rust, Smartcore, Medium, The Startup, 2021/1/15 | * [https://medium.com/swlh/machine-learning-in-rust-smartcore-2f472d1ce83 Machine Learning in Rust, Smartcore, Medium, The Startup, 2021/1/15] (c) [https://volodymyr-orlov.medium.com/ Vlad Orlov]<br> | ||
Machine Learning in Rust, Logistic Regression, Medium, The Startup, 2021/1/6 | * [https://medium.com/swlh/machine-learning-in-rust-logistic-regression-74d6743df161 Machine Learning in Rust, Logistic Regression, Medium, The Startup, 2021/1/6] (c) [https://volodymyr-orlov.medium.com/ Vlad Orlov]<br> | ||
Machine Learning in Rust, Linear Regression, Medium, The Startup, 2020/12/16 | * [https://medium.com/swlh/machine-learning-in-rust-linear-regression-edef3fb65f93 Machine Learning in Rust, Linear Regression, Medium, The Startup, 2020/12/16] (c) [https://volodymyr-orlov.medium.com/ Vlad Orlov]<br> | ||
Machine Learning in Rust, 2016/3/7, James, Examples of LogisticRegressor | * [https://athemathmo.github.io/2016/03/07/rusty-machine.html Machine Learning in Rust, 2016/3/7, James, Examples of LogisticRegressor]<br> | ||
Machine Learning and Rust (Part 1): Getting Started!, Level Up Coding, 2021/1/9, Stefano Bosisio | * [https://levelup.gitconnected.com/machine-learning-and-rust-part-1-getting-started-745885771bc2 Machine Learning and Rust (Part 1): Getting Started!, Level Up Coding, 2021/1/9, Stefano Bosisio]<br> | ||
Machine Learning and Rust (Part 2): Linear Regression, Level Up Coding, 2021/6/15, Stefano Bosisio | * [https://levelup.gitconnected.com/machine-learning-and-rust-part-2-linear-regression-d3b820ed28f9 Machine Learning and Rust (Part 2): Linear Regression, Level Up Coding, 2021/6/15, Stefano Bosisio]<br> | ||
Machine Learning and Rust (Part 3): Smartcore, Dataframe, and Linear Regression, Level Up Coding, 2021/7/1, Stefano Bosisio | * [https://levelup.gitconnected.com/machine-learning-and-rust-part-3-smartcore-dataframe-and-linear-regression-10451fdc2e60 Machine Learning and Rust (Part 3): Smartcore, Dataframe, and Linear Regression, Level Up Coding, 2021/7/1, Stefano Bosisio]<br> | ||
Tensorflow Rust Practical Part 1, Programmer Sought, 2018 | * [https://www.programmersought.com/article/18696273900/ Tensorflow Rust Practical Part 1, Programmer Sought, 2018]<br> | ||
A Machine Learning introduction to ndarray, RustFest 2019, 2019/11/12 | * [https://barcelona.rustfest.eu/sessions/machine-learning-ndarray A Machine Learning introduction to ndarray, RustFest 2019, 2019/11/12] (c) [https://github.com/LukeMathWalker Luca Palmieri]<br> | ||
Simple Linear Regression from scratch in Rust, Web Development, Software Architecture, Algorithms and more, 2018/12/13, philipp | * [https://cheesyprogrammer.com/2018/12/13/simple-linear-regression-from-scratch-in-rust/ Simple Linear Regression from scratch in Rust, Web Development, Software Architecture, Algorithms and more, 2018/12/13, philipp]<br> | ||
Interactive Rust in a REPL and Jupyter Notebook with EVCXR, Depth-First, 2020/9/21, Richard L. Apodaca | * [https://depth-first.com/articles/2020/09/21/interactive-rust-in-a-repl-and-jupyter-notebook-with-evcxr/ Interactive Rust in a REPL and Jupyter Notebook with EVCXR, Depth-First, 2020/9/21, Richard L. Apodaca]<br> | ||
Rust for Data Science: Tutorial 1, dev, 2021/8/25, Davide Del Papa | * [https://dev.to/davidedelpapa/rust-for-data-science-tutorial-1-4g5j Rust for Data Science: Tutorial 1, dev, 2021/8/25, Davide Del Papa]<br> | ||
petgraph_review, 2019/10/11, Timothy Hobbs | * [https://timothy.hobbs.cz/rust-play/petgraph_review.html petgraph_review, 2019/10/11, Timothy Hobbs]<br> | ||
Rust for ML. Rust, Medium, Tempus Ex, 2021/8/1, Michael Naquin | * [https://medium.com/tempus-ex/rust-for-ml-fba0421b0959 Rust for ML. Rust, Medium, Tempus Ex, 2021/8/1, Michael Naquin]<br> | ||
Adventures in Drone Photogrammetry Using Rust and Machine Learning (Image Segmentation with linfa and DBSCAN), 2021/11/14, CHRISTOPHER MORAN | * [http://cmoran.xyz/writing/adventures_in_photogrammetry Adventures in Drone Photogrammetry Using Rust and Machine Learning (Image Segmentation with linfa and DBSCAN), 2021/11/14, CHRISTOPHER MORAN]<br> | ||
== | ==ПРИКЛАДНЫЕ РЕСУРСЫ== | ||
Deep Learning in Rust: baby steps, Medium, 2016/2/2, Theodore DeRego | * [https://medium.com/@tedsta/deep-learning-in-rust-7e228107cccc Deep Learning in Rust: baby steps, Medium, 2016/2/2, Theodore DeRego]<br> | ||
A Rust SentencePiece implementation, Rust NLP tales, 2020/5/30 | * [https://guillaume-be.github.io/2020-05-30/sentence_piece A Rust SentencePiece implementation, Rust NLP tales, 2020/5/30]<br> | ||
Accelerating text generation with Rust, Rust NLP tales, 2020/11/21 | * [https://guillaume-be.github.io/2020-11-21/generation_benchmarks Accelerating text generation with Rust, Rust NLP tales, 2020/11/21]<br> | ||
A Simple Text Summarizer written in Rust, Towards Data Science, 2020/11/24 | * [https://towardsdatascience.com/a-simple-text-summarizer-written-in-rust-4df05f9327a5 A Simple Text Summarizer written in Rust, Towards Data Science, 2020/11/24,Examples of Text Sentence Vector, Cosine Distance and PageRank] (c)[https://chancharles.medium.com/ Charles Chan]<br> | ||
Extracting deep learning image embeddings in Rust, RecoAI, 2021/6/1, Paweł Jankiewic, Examples of ONNX | * [https://logicai.io/blog/extracting-image-embeddings/ Extracting deep learning image embeddings in Rust, RecoAI, 2021/6/1, Paweł Jankiewic, Examples of ONNX]<br> | ||
Deep Learning in Rust with GPU, 2021/7/30, Xavier Tao | * [https://able.bio/haixuanTao/deep-learning-in-rust-with-gpu--26c53a7f Deep Learning in Rust with GPU, 2021/7/30, Xavier Tao]<br> | ||
tch-rs pretrain example - Docker for PyTorch rust bindings tch-rs. Example of pretrain model, 2021/8/15, vaaaaanquish | * [https://github.com/vaaaaanquish/tch-rs-pretrain-example-docker tch-rs pretrain example - Docker for PyTorch rust bindings tch-rs. Example of pretrain model, 2021/8/15, vaaaaanquish]<br> | ||
Rust ANN search Example - Image search example by approximate nearest-neighbor library In Rust, 2021/8/15, vaaaaanquish | * [https://github.com/vaaaaanquish/rust-ann-search-example Rust ANN search Example - Image search example by approximate nearest-neighbor library In Rust, 2021/8/15, vaaaaanquish]<br> | ||
dzamkov/deep-learning-test - Implementing deep learning in Rust using just a linear algebra library (nalgebra), 2021/8/30, dzamkov | * [https://github.com/dzamkov/deep-learning-test dzamkov/deep-learning-test - Implementing deep learning in Rust using just a linear algebra library (nalgebra), 2021/8/30, dzamkov]<br> | ||
vaaaaanquish/rust-machine-learning-api-example - The axum example that uses resnet224 to infer images received in base64 and returns the results., 2021/9/7, vaaaaanquish | * [https://github.com/vaaaaanquish/rust-machine-learning-api-example vaaaaanquish/rust-machine-learning-api-example - The axum example that uses resnet224 to infer images received in base64 and returns the results., 2021/9/7, vaaaaanquish]<br> | ||
Rust for Machine Learning: Benchmarking Performance in One-shot - A Rust implementation of Siamese Neural Networks for One-shot Image Recognition for benchmarking performance and results, UofT Machine Intelligence Student Team | * [https://utmist.gitlab.io/projects/rust-ml-oneshot/ Rust for Machine Learning: Benchmarking Performance in One-shot - A Rust implementation of Siamese Neural Networks for One-shot Image Recognition for benchmarking performance and results, UofT Machine Intelligence Student Team]<br> | ||
Why Wallaroo Moved From Pony To Rust, 2021/8/19, Wallaroo.ai | * [https://wallarooai.medium.com/why-wallaroo-moved-from-pony-to-rust-292e7339fc34 Why Wallaroo Moved From Pony To Rust, 2021/8/19, Wallaroo.ai]<br> | ||
epwalsh/rust-dl-webserver - Example of serving deep learning models in Rust with batched prediction, 2021/11/16, epwalsh | * [https://github.com/epwalsh/rust-dl-webserver epwalsh/rust-dl-webserver - Example of serving deep learning models in Rust with batched prediction, 2021/11/16, epwalsh]<br> | ||
Production users - Rust Programming Language, by rust-lang.org | * [https://www.rust-lang.org/production/users Production users - Rust Programming Language, by rust-lang.org]<br> | ||
Taking ML to production with Rust: a 25x speedup, A LEARNING JOURNAL, 2019/12/1 | * [https://www.lpalmieri.com/posts/2019-12-01-taking-ml-to-production-with-rust-a-25x-speedup/ Taking ML to production with Rust: a 25x speedup, A LEARNING JOURNAL, 2019/12/1] (c) [https://twitter.com/algo_luca @algo_luca]<br> | ||
9 Companies That Use Rust in Production, serokell, 2020/11/18, Gints Dreimanis | * [https://serokell.io/blog/rust-companies 9 Companies That Use Rust in Production, serokell, 2020/11/18, Gints Dreimanis]<br> | ||
Masked Language Model on Wasm, BERT on flontend examples, optim-corp/masked-lm-wasm, 2021/8/27, Optim | * [https://github.com/optim-corp/masked-lm-wasm/ Masked Language Model on Wasm, BERT on flontend examples, optim-corp/masked-lm-wasm, 2021/8/27, Optim]<br> | ||
Serving TensorFlow with Actix-Web, kykosic/actix-tensorflow-example | * [https://github.com/kykosic/actix-tensorflow-example Serving TensorFlow with Actix-Web, kykosic/actix-tensorflow-example]<br> | ||
Serving PyTorch with Actix-Web, kykosic/actix-pytorch-example | * [https://github.com/kykosic/actix-pytorch-example Serving PyTorch with Actix-Web, kykosic/actix-pytorch-example]<br> | ||
== | ==ФОРУМЫ== | ||
Natural Language Processing in Rust : rust, 2016/12/6 | * [https://www.reddit.com/r/rust/comments/5jj8vr/natural_language_processing_in_rust Natural Language Processing in Rust : rust, 2016/12/6]<br> | ||
Future prospect of Machine Learning in Rust Programming Language : MachineLearning, 2017/11/11 | * [https://www.reddit.com/r/MachineLearning/comments/7iz51p/d_future_prospect_of_machine_learning_in_rust/ Future prospect of Machine Learning in Rust Programming Language : MachineLearning, 2017/11/11]<br> | ||
Interest for NLP in Rust? - The Rust Programming Language Forum, 2018/1/19 | * [https://users.rust-lang.org/t/interest-for-nlp-in-rust/15331 Interest for NLP in Rust? - The Rust Programming Language Forum, 2018/1/19]<br> | ||
Is Rust good for deep learning and artificial intelligence? - The Rust Programming Language Forum, 2018/11/18 | * [https://users.rust-lang.org/t/is-rust-good-for-deep-learning-and-artificial-intelligence/22866 Is Rust good for deep learning and artificial intelligence? - The Rust Programming Language Forum, 2018/11/18]<br> | ||
ndarray vs nalgebra : rust, 2019/5/28 | * [https://www.reddit.com/r/rust/comments/btn1cz/ndarray_vs_nalgebra/ ndarray vs nalgebra : rust, 2019/5/28]<br> | ||
Taking ML to production with Rust | Hacker News, 2019/12/2 | * [https://news.ycombinator.com/item?id=21680965 Taking ML to production with Rust | Hacker News, 2019/12/2]<br> | ||
Who is using Rust for Machine learning in production/research? : rust, 2020/4/5 | * [https://www.reddit.com/r/rust/comments/fvehyq/d_who_is_using_rust_for_machine_learning_in/ Who is using Rust for Machine learning in production/research? : rust, 2020/4/5]<br> | ||
Deep Learning in Rust, 2020/8/26 | * [https://www.reddit.com/r/rust/comments/igz8iv/deep_learning_in_rust/ Deep Learning in Rust, 2020/8/26]<br> | ||
SmartCore, fast and comprehensive machine learning library for Rust! : rust, 2020/9/29 | * [https://www.reddit.com/r/rust/comments/j1mj1g/smartcore_fast_and_comprehensive_machine_learning/ SmartCore, fast and comprehensive machine learning library for Rust! : rust, 2020/9/29]<br> | ||
Deep Learning in Rust with GPU on ONNX, 2021/7/31 | * [https://www.reddit.com/r/MachineLearning/comments/ouul33/d_p_deep_learning_in_rust_with_gpu_on_onnx/ Deep Learning in Rust with GPU on ONNX, 2021/7/31]<br> | ||
Rust vs. C++ the main differences between these popular programming languages, 2021/8/25 | * [https://codilime.com/blog/rust-vs-cpp-the-main-differences-between-these-popular-programming-languages/ Rust vs. C++ the main differences between these popular programming languages, 2021/8/25]<br> | ||
I wanted to share my experience of Rust as a deep learning researcher, 2021/9/2 | * [https://www.reddit.com/r/rust/comments/pft9n9/i_wanted_to_share_my_experience_of_rust_as_a_deep/ I wanted to share my experience of Rust as a deep learning researcher, 2021/9/2]<br> | ||
How far along is the ML ecosystem with Rust?, 2021/9/15 | * [https://www.reddit.com/r/rust/comments/poglgg/how_far_along_is_the_ml_ecosystem_with_rust/ How far along is the ML ecosystem with Rust?, 2021/9/15]<br> | ||
== | ==КНИГИ== | ||
Practical Machine Learning with Rust: Creating Intelligent Applications in Rust (English Edition) | * [https://amzn.to/3h7JV8U '''Practical Machine Learning with Rust: Creating Intelligent Applications in Rust (English Edition)''']<br> | ||
Use Rust libraries for different tasks in machine learning | -- 2019/12/10, Joydeep BhattacharjeeWrite machine learning algorithms in Rust<br> | ||
Create concise Rust packages for your machine learning applications | - Use Rust libraries for different tasks in machine learning<br> | ||
Implement NLP and computer vision in Rust | - Create concise Rust packages for your machine learning applications<br> | ||
Deploy your code in the cloud and on bare metal servers | - Implement NLP and computer vision in Rust<br> | ||
- Deploy your code in the cloud and on bare metal servers<br> | |||
DATA ANALYSIS WITH RUST NOTEBOOKS | * [https://github.com/Apress/practical-machine-learning-w-rust source code for this Book]<br> | ||
Operations with ndarray | -- | ||
Descriptive Statistics | * [https://datacrayon.com/shop/product/data-analysis-with-rust-notebooks/ '''DATA ANALYSIS WITH RUST NOTEBOOKS''']<br> | ||
Interactive Diagram | -- 2021/9/3, Shahin RostamiPlotting with Plotters and Plotly<br> | ||
Visualisation of Co-occurring Types | - Operations with ndarray<br> | ||
download source code and dataset | - Descriptive Statistics<br> | ||
- Interactive Diagram<br> | |||
- Visualisation of Co-occurring Types<br> | |||
- download source code and dataset<br> | |||
* [https://datacrayon.com/posts/programming/rust-notebooks/preface/ Full text book]<br> | |||
==ВИДЕО УРОКИ== | |||
* [https://www.youtube.com/watch?v=lY10kTcM8ek The /r/playrust Classifier: Real World Rust Data Science, RustConf 2016, 2016/10/05, Suchin Gururangan & Colin O'Brien]<br> | |||
* [https://www.youtube.com/watch?v=UHFlKAmANJg Building AI Units in Rust, FOSSASIA 2018, 2018/3/25, Vigneshwer Dhinakaran]<br> | |||
The /r/playrust Classifier: Real World Rust Data Science, RustConf 2016, 2016/10/05, Suchin Gururangan & Colin O'Brien | * [https://www.youtube.com/watch?v=kytvDxxedWY Python vs Rust for Simulation, EuroPython 2019, 2019/7/10, Alisa Dammer]<br> | ||
Building AI Units in Rust, FOSSASIA 2018, 2018/3/25, Vigneshwer Dhinakaran | * [https://www.youtube.com/watch?v=odI_LY8AIqo Machine Learning is changing - is Rust the right tool for the job?, RustLab 2019, 2019/10/31, Luca Palmieri]<br> | ||
Python vs Rust for Simulation, EuroPython 2019, 2019/7/10, Alisa Dammer | * [https://www.youtube.com/watch?v=DUVE86yTfKU Using TensorFlow in Embedded Rust, 2020/09/29, Ferrous Systems GmbH, Richard Meadows]<br> | ||
Machine Learning is changing - is Rust the right tool for the job?, RustLab 2019, 2019/10/31, Luca Palmieri | * [https://www.youtube.com/watch?v=D1NAREuicNs Writing the Fastest GBDT Library in Rust, 2021/09/16, RustConf 2021, Isabella Tromba]<br> | ||
Using TensorFlow in Embedded Rust, 2020/09/29, Ferrous Systems GmbH, Richard Meadows | |||
Writing the Fastest GBDT Library in Rust, 2021/09/16, RustConf 2021, Isabella Tromba | |||
==Подкасты== | ==Подкасты== | ||
DATA SCIENCE AT | DATA SCIENCE AT HOME: | ||
* [https://datascienceathome.com/rust-and-machine-learning-1-ep-107/ Rust and machine learning #1 (Ep. 107)]<br> | |||
* [https://datascienceathome.com/rust-and-machine-learning-2-with-luca-palmieri-ep-108/ Rust and machine learning #2 with Luca Palmieri (Ep. 108)]<br> | |||
* [https://datascienceathome.com/rust-and-machine-learning-3-with-alec-mocatta-ep-109/ Rust and machine learning #3 with Alec Mocatta (Ep. 109)]<br> | |||
* [https://datascienceathome.com/rust-and-machine-learning-4-practical-tools-ep-110/ Rust and machine learning #4: practical tools (Ep. 110)]<br> | |||
* [https://datascienceathome.com/machine-learning-in-rust-amadeus-with-alec-mocatta-rb-ep-127/ Machine Learning in Rust: Amadeus with Alec Mocatta (Ep. 127)]<br> | |||
* [https://datascienceathome.com/rust-and-deep-learning/ Rust and deep learning with Daniel McKenna (Ep. 135)]<br> | |||
* [https://datascienceathome.com/is-rust-flexible-enough-for-a-flexible-data-model-ep-137/ Is Rust flexible enough for a flexible data model? (Ep. 137)]<br> | |||
* [https://datascienceathome.com/pandas-vs-rust-ep-144/ Pandas vs Rust (Ep. 144)]<br> | |||
* [https://datascienceathome.com/apache-arrow-ballista-and-big-data-in-rust-with-andy-grove-ep-145/ Apache Arrow, Ballista and Big Data in Rust with Andy Grove (Ep. 145)]<br> | |||
* [https://datascienceathome.com/polars-the-fastest-dataframe-crate-in-rust-ep-146/ Polars: the fastest dataframe crate in Rust (Ep. 146)]<br> | |||
* [https://datascienceathome.com/apache-arrow-ballista-and-big-data-in-rust-with-andy-grove-rb-ep-160/ Apache Arrow, Ballista and Big Data in Rust with Andy Grove RB (Ep. 160)]<br> | |||
==ИСТОЧНИКИ== | ==ИСТОЧНИКИ== | ||
* [https://dzen.ru/a/YnY7nBxvdEJtsFTu Огромный респект Автору] | * [https://dzen.ru/a/YnY7nBxvdEJtsFTu Огромный респект Автору] |
Текущая версия от 19:34, 23 мая 2023
ВВЕДЕНИЕ
Эта статья содержит список библиотек машинного обучения, написанных на Rust.
Представляет собой сборник репозитариев GitHub, блогов, книг, уроков, форумов, статей.
Статья разбита на несколько основных категорий библиотек и алгоритмов. В статье нет библиотек,
которые больше не поддерживаются, а так же почти нет небольших библиотек, которые давно не обновлялись.
ЛИНЕЙНАЯ АЛГЕБРА
- Большинство пакетов в списке используют ndarray или std::vec.
- dimforge/nalgebra - Библиотека линейной алгебры для Rust.
- rust-ndarray/ndarray - ndarray: работа с многомерными массивами на Rust
- AtheMathmo/rulinalg - Библиотека линейной алгебры написанная на Rust
- arrayfire/arrayfire-rust - Обертка Rust для ArrayFire
- bluss/arrayvec - работа с векторами. (Rust)
- vbarrielle/sprs - библиотека линейной алгебры для Rust
- liborty/rstats - Библиотека статистики Rust и векторной алгебры
- PyO3/rust-numpy - NumPy C-API для Rust на основе PyO3
ИНСТРУМЕНТЫ ПОДДЕРЖКИ
- Jupyter Notebook
- evcxr может обрабатывать как Jupyter Kernel или REPL.
Эти библиотеки нужны для обучения алгоритмов и проверки гипотез машинного обучения.
- google/evcxr - оценки моделей для Rust.
- emakryo/rustdef - Jupyter расширение для rust.
- murarth/rusti - REPL библиотека для Rust
РАБОТА С ВИЗУАЛИЗАЦИЕЙ
- Список полезных ресурсов для визуализации данных.
- 38/plotters - A rust drawing library for high quality data plotting for both WASM and native, statically and realtimely|
- igiagkiozis/plotly - Plotly for Rust
- milliams/plotlib - Data plotting library for Rust
- tiby312/poloto - A simple 2D plotting library that outputs graphs to SVG that can be styled using CSS.
- askanium/rustplotlib - A pure Rust visualization library inspired by D3.js
- SiegeLord/RustGnuplot - A Rust library for drawing plots, powered by Gnuplot.
- saona-raimundo/preexplorer - Externalize easily the plotting process from Rust to gnuplot.
- procyon-rs/vega_lite_4.rs - rust api for vega-lite
- v4procyon-rs/showata - A library of to show data (in browser, evcxr_jupyter) as table, chart...
- coder543/dataplotlib - Scientific plotting library for Rust
- shahinrostami/chord_rs - Rust crate for creating beautiful interactive Chord Diagrams.
- Chord Diagrams - Pro version available
- ASCII line graph:
- loony-bean/textplots-rs Terminal plotting library for Rust
- orhanbalci/rasciigraph Zero dependency Rust crate to make lightweight ASCII line graph ╭┈╯ in command line apps with no other dependencies.
- jakobhellermann/piechart a rust crate for drawing fancy pie charts in the terminal
- milliams/plot Command-line plotting tool written in Rust
- Примеры:
- Plotters Developer's Guide
- Plotly.rs - Plotly.rs Book
- petgraph_review
- evcxr-jupyter-integration
- Rust for Data Science: Tutorial 1 - DEV Community
- Preface | Data Crayon
- Дата-фреймы:
- ritchie46/polars - Rust датафреймы library
- apache/arrow - In-memory columnar format, in Rust.
- apache/arrow-datafusion - Apache Arrow DataFusion and Ballista query engines
- milesgranger/black-jack - DataFrame / Series data processing in Rust
- nevi-me/rust-dataframe - A Rust DataFrame implementation, built on Apache Arrow
- kernelmachine/utah - Dataframe structure and operations in Rust
- sinhrks/brassfibre - Provides multiple-dtype columner storage, known as DataFrame in pandas/R
ОБРАБОТКА ИЗОБРАЖЕНИЙ
- Для обработка изображений вам стоит попробовать библиотеку image-rs.
Здесь приведены такие алгоритмы, как линейные преобразования, подобное есть и в других библиотеках.
- image-rs/image - Encoding and decoding images in Rust
- Image processing operations
- Allows conversion between ndarray's types and image's types
- Rust CV mono-repo. Contains pure-Rust dependencies which attempt to encapsulate the capability of OpenCV, OpenMVG, and vSLAM frameworks in a cohesive set of APIs.
- Rust bindings for OpenCV 3 & 4
- A linear algebra and mathematics library for computer graphics.
- Face detection library for the Rust programming language
ОБРАБОТКА ЕСТЕСТВЕННОГО ЯЗЫКА ИЛИ ПРЕДВАРИТЕЛЬНАЯ ОБРАБОТКА
- Этот репозиторий содержит обработки естественного языка (google)
- pemistahl/lingua-rs The most accurate natural language detection library in the Rust ecosystem, suitable for long and short text alike
- usamec/cntk-rs - Wrapper around Microsoft CNTK library
- stickeritis/sticker - A LSTM/Transformer/dilated convolution sequence labeler
- tensordot/syntaxdot - Neural syntax annotator, supporting sequence labeling, lemmatization, and dependency parsing.
- christophertrml/rs-natural - Natural Language Processing for Rust
- bminixhofer/nnsplit - Semantic text segmentation. For sentence boundary detection, compound splitting and more.
- greyblake/whatlang-rs - Natural language detection library for Rust.
- finalfusion/finalfrontier - Context-sensitive word embeddings with subwords. In Rust.
- bminixhofer/nlprule - A fast, low-resource Natural Language Processing and Error Correction library written in Rust.
- rth/vtext - Simple NLP in Rust with Python bindings
- tamuhey/tokenizations - Robust and Fast tokenizations alignment library for Rust and Python
- vgel/treebender - A HDPSG-inspired symbolic natural language parser written in Rust
- reinfer/blingfire-rs - Rust wrapper for the BlingFire tokenization library
- CurrySoftware/rust-stemmers - Common stop words in a variety of languages
- cmccomb/rust-stop-words - Common stop words in a variety of languages
- Freyskeyd/nlp - Rust-nlp is a library to use Natural Language Processing algorithm with RUST
- Daniel-Liu-c0deb0t/uwu - fastest text uwuifier in the west
ГРАФЫ
- GraphScope: A One-Stop Large-Scale Graph Computing System from Alibaba
- petgraph/petgraph Graph data structure library for Rust.
- rs-graph/rs-graph - rs-graph is a library for graph algorithms and combinatorial optimization
- metamolecular/gamma A graph library for Rust.
- purpleprotocol/graphlib Simple but powerful graph library for Rust
- yamafaktory/hypergraph Hypergraph is a data structure library to generate directed hypergraphs
AutoML
- tangramxyz/tangram - Tangram is an all-in-one automated machine learning framework.
- datafuselabs/datafuse - A Modern Real-Time Data Processing & Analytics DBMS with Cloud-Native Architecture (Rust)
- mstallmo/tensorrt-rs - Rust library for running TensorRT accelerated deep learning models
- pipehappy1/tensorboard-rs - Write TensorBoard events in Rust.
- ehsanmok/tvm-rust - Rust bindings for TVM runtime
- vertexclique/orkhon - Orkhon: ML Inference Framework and Server Runtime
- Xaynet represents an agnostic Federated Machine Learning framework to build privacy-preserving AI applications
- webonnx/wonnx - A GPU-accelerated ONNX inference run-time written 100% in Rust, ready for the web
- sonos/tract - Tiny, no-nonsense, self-contained, Tensorflow and ONNX inference
- MegEngine/MegFlow - Efficient ML solutions for long-tailed demands
РАБОЧИЕ ПОТОКИ
- substantic/rain - Framework for large distributed pipelines
- timberio/vector - A high-performance, highly reliable, observability data pipeline
ВЫЧИСЛЕНИЯ НА GPU С ПОМОЩЬЮ RUST
- Rust-GPU/Rust-CUDA - Ecosystem of libraries and tools for writing and executing extremely fast GPU code fully in Rust.
- EmbarkStudios/rust-gpu Making Rust a first-class language and ecosystem for GPU code
- termoshtt/accel GPGPU Framework for Rust
- kmcallister/glassful Rust-like syntax for OpenGL Shading Language
- Rust to SPIR-V compiler
- japaric-archived/nvptx - How to: Run Rust code on your NVIDIA GPU
- msiglreith/inspirv-rust Rust (MIR) → SPIR-V (Shader) compiler
SKLEARN И ПОДОБНЫЕ БИБЛИОТЕКИ
- Библиотеки поддерживают следующие алгоритмы:
Linear Regression Logistic Regression K-Means Clustering Neural Networks Gaussian Process Regression Support Vector Machines kGaussian Mixture Models Naive Bayes Classifiers DBSCAN k-Nearest Neighbor Classifiers Principal Component Analysis Decision Tree Support Vector Machines Naive Bayes Elastic Net
- rust-ml/linfa - A Rust machine learning framework.Gaussian Mixture Model Clustering, Agglomerative Hierarchical Clustering, ICA
- maciejkula/rustlearn - Machine learning crate for Rustfactorization machines, k-fold cross-validation, ndcg
СТАТИСТИКА
- statrs-dev/statrs - Statistical computation library for Rust
- rust-ndarray/ndarray-stats - Statistical routines for ndarray
- Axect/Peroxide - Rust numeric library with R, MATLAB & Python syntaxLinear Algebra, Functional Programming, Automatic Differentiation, Numerical Analysis, Statistics, Special functions, Plotting, Dataframe
- tarcieri/micromath - Embedded Rust arithmetic, 2D/3D vector, and statistics library
ГРАДИЕНТНЫЙ БУСТИНГ(Gradient Boosting)
- mesalock-linux/gbdt-rs - MesaTEE GBDT-RS : a fast and secure GBDT library, supporting TEEs such as Intel SGX and ARM TrustZone
- davechallis/rust-xgboost - Rust bindings for XGBoost.
- vaaaaanquish/lightgbm-rs - LightGBM Rust binding
- catboost/catboost - A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks (predict only)
- Entscheider/stamm - Generic decision trees for rust
НЕЙРОННЫЕ СЕТИ
- Tensorflow и PyTorch являются наиболее распространенными библиотеками для построения нейронных сетей.
- Rust language bindings for TensorFlow
- LaurentMazare/tch-rs - Rust bindings for the C++ api of PyTorch.
- VasanthakumarV/einops - Simplistic API for deep learning tensor operations
- spearow/juice - The Hacker's Machine Learning Engine
- neuronika/neuronika - Tensors and dynamic neural networks in pure Rust.
- bilal2vec/L2 - l2 is a fast, Pytorch-style Tensor+Autograd library written in Rust
- raskr/rust-autograd - Tensors and differentiable operations (like TensorFlow) in Rust
- charles-r-earp/autograph - Machine Learning Library for Rust
- patricksongzy/corgi - A neural network, and tensor dynamic automatic differentiation implementation for Rust.
- JonathanWoollett-Light/cogent - Simple neural network library for classification written in Rust.
- oliverfunk/darknet-rs - Rust bindings for darknet
- jakelee8/mxnet-rs - mxnet for Rust
- jramapuram/hal - Rust based Cross-GPU Machine Learning
- primitiv/primitiv-rust - Rust binding of primitiv
- The Rust Language Bindings for DyNet
- millardjn/alumina - A deep learning library for rust
- jramapuram/hal - Rust based Cross-GPU Machine Learning
- afck/fann-rs - Rust wrapper for the Fast Artificial Neural Network library
- autumnai/leaf - Open Machine Intelligence Framework for Hackers. (GPU/CPU)
- c0dearm/mushin - Compile-time creation of neural networks
- tedsta/deeplearn-rs - Neural networks in Rust
- sakex/neat-gru-rust - neat-gru
- nerosnm/n2 - (Work-in-progress) library implementation of a feedforward, backpropagation artificial neural network
- Wuelle/deep_thought - Neural Networks in Rust
- MikhailKravets/NeuroFlow - Awesome deep learning crate
- dvigneshwer/deeprust - Machine learning crate in Rust
- millardjn/rusty_sr - Deep learning superresolution in pure rust
ГРАФОВЫЕ МОДЕЛИ
- Synerise/cleora Cleora AI is a general-purpose model for efficient, scalable learning of stable and inductive entity embeddings for heterogeneous relational data.
- Rust library for random graph ensembles
НЕЙРОЛИНГВИСТИЧЕСКОЕ ПРОГРАММИРОВАНИЕ
- huggingface/tokenizers - The core of tokenizers, written in Rust. Provides an implementation of today's most used tokenizers, with a focus on performance and versatility.
- guillaume-be/rust-tokenizers - Rust-tokenizer offers high-performance tokenizers for modern language models, including WordPiece, Byte-Pair Encoding (BPE) and Unigram (SentencePiece) models
- guillaume-be/rust-bert - Rust native ready-to-use NLP pipelines and transformer-based models (BERT, DistilBERT, GPT2,...)
- sno2/bertml - Use common pre-trained ML models in Deno!
- cpcdoy/rust-sbert
- Rust port of sentence-transformers
- vongaisberg/gpt3_macro - Rust macro that uses GPT3 codex to generate code at compiletime
- proycon/deepfrog - An NLP-suite powered by deep learning
- ferristseng/rust-tfidf - Library to calculate TF-IDF
- messense/fasttext-rs - fastText Rust binding
- mklf/word2vec-rs - pure rust implementation of word2vec
- DimaKudosh/word2vec - Rust interface to word2vec.
- lloydmeta/sloword2vec-rs - A naive (read: slow) implementation of Word2Vec. Uses BLAS behind the scenes for speed.
РЕКОМЕНДАТЕЛЬНЫЕ СИСТЕМЫ
- PersiaML/PERSIA - High performance distributed framework for training deep learning recommendation models based on PyTorch.
- jackgerrits/vowpalwabbit-rs Rusty VowpalWabbit
- outbrain/fwumious_wabbit - Fwumious Wabbit, fast on-line machine learning toolkit written in Rust
- hja22/rucommender - Rust implementation of user-based collaborative filtering
- maciejkula/sbr-rs - Deep recommender systems for Rust
- chrisvittal/quackin - A recommender systems framework for Rust
- snd/onmf - fast rust implementation of online nonnegative matrix factorization as laid out in the paper "detect and track latent factors with online nonnegative matrix factorization"
- rhysnewell/nymph - Non-Negative Matrix Factorization in Rust
РАБОТА С ТЕКСТОМ
- Quickwit is a big data search engine.
- bayard-search/bayard Full-text search and indexing server written in Rust.
- neuml/txtai.rs AI-powered search engine for Rust
- meilisearch/MeiliSearch - Lightning Fast, Ultra Relevant, and Typo-Tolerant Search Engine
- toshi-search/Toshi Full-text search engine in rust
- BurntSushi/fst Represent large sets and maps compactly with finite state transducers.
- tantivy-search/tantivy Tantivy is a full-text search engine library inspired by Apache Lucene and written in Rust
- tinysearch/tinysearch 🔍 Tiny, full-text search engine for static websites built with Rust and Wasm
- quantleaf/probly-search Lightweight full-text search library that provides full control over the scoring calculations
- Simple and lightweight fuzzy search engine that works in memory, searching for similar strings
- jameslittle230/stork Impossibly fast web search, made for static sites.
- elastic/elasticsearch-rs - Official Elasticsearch Rust Client
АЛГОРИТМЫ ПОИСКА БЛИЖАЙШИХ СОСЕДЕЙ
- Enet4/faiss-rs - Rust language bindings for Faiss
- rust-cv/hnsw - HNSW ANN from the paper "Efficient and robust approximate nearest neighbor search using Hierarchical Navigable Small World graphs"
- hora-search/hora Efficient approximate nearest neighbor search algorithm collections library, which implemented with Rust. horasearch.com
- InstantDomain/instant-distance - Fast approximate nearest neighbor searching in Rust, based on HNSW index
- lerouxrgd/ngt-rs - Rust wrappers for NGT approximate nearest neighbor search
- granne/granne - Graph-based Approximate Nearest Neighbor Search
- u1roh/kd-tree - k-dimensional tree in Rust. Fast, simple, and easy to use.
- qdrant/qdrant - Qdrant - vector similarity search engine with extended filtering support
- rust-cv/hwt - Hamming Weight Tree from the paper "Online Nearest Neighbor Search in Hamming Space"
- fulara/kdtree-rust - kdtree implementation for rust.
- mrhooray/kdtree-rs - K-dimensional tree in Rust for fast geospatial indexing and lookup
- kornelski/vpsearch - C library for finding nearest (most similar) element in a set
- petabi/petal-neighbors - Nearest neighbor search algorithms including a ball tree and a vantage point tree.
- ritchie46/lsh-rs - Locality Sensitive Hashing in Rust with Python bindings
- kampersanda/mih-rs - Rust implementation of multi-index hashing for neighbor searches on 64-bit codes in the Hamming space
ОБУЧЕНИЕ С ПОДКРЕПЛЕНИЕМ
- taku-y/border Border is a reinforcement learning library in Rust
- NivenT/REnforce Reinforcement learning library written in Rust
- edlanglois/relearn Reinforcement learning with Rust
- tspooner/rsrl Fast, safe and easy to use reinforcement learning framework in Rust.
- milanboers/rurel Flexible, reusable reinforcement learning (Q learning) implementation in Rust
- Bandit Algorithms in Rust
- MrRobb/gym-rs - OpenAI Gym bindings for Rust
ОБУЧЕНИЕ С УЧИТЕЛЕМ
- tomtung/omikuji - An efficient implementation of Partitioned Label Trees & its variations for extreme multi-label classification
- shadeMe/liblinear-rs - Rust language bindings for the LIBLINEAR C/C++ library.
- messense/crfsuite-rs - Rust binding to crfsuite
- ralfbiedert/ffsvm-rust - FFSVM stands for "Really Fast Support Vector Machine"
- zenoxygen/bayespam - A simple bayesian spam classifier written in Rust.
- Rui_Vieira/naive-bayesnaive-bayes - A Naive Bayes classifier written in Rust.
- Rui_Vieira/random-forests - A Rust library for Random Forests.
- sile/randomforest - A random forest implementation in Rust
- tomtung/craftml-rs - A Rust🦀 implementation of CRAFTML, an Efficient Clustering-based Random Forest for Extreme Multi-label Learning
- nkaush/naive-bayes-rs - A Rust library with homemade machine learning models to classify the MNIST dataset. Built in an attempt to get familiar with advanced Rust concepts.
ОБУЧЕНИЕ БЕЗ УЧИТЕЛЯ
- frjnn/bhtsne - Barnes-Hut t-SNE implementation written in Rust.
- vaaaaanquish/label-propagation-rs - Label Propagation Algorithm by Rust. Label propagation (LP) is graph-based semi-supervised learning (SSL). LGC and CAMLP have been implemented.
- nmandery/extended-isolation-forest - Rust port of the extended isolation forest algorithm for anomaly detection
- avinashshenoy97/RusticSOM - Rust library for Self Organising Maps (SOM).
- diffeo/kodama - Fast hierarchical agglomerative clustering in Rust.
- kno10/rust-kmedoids - k-Medoids clustering in Rust with the FasterPAM algorithm
- petabi/petal-clustering - DBSCAN and OPTICS clustering algorithms.
- savish/dbscan - A naive DBSCAN implementation in Rust
- gu18168/DBSCANSD - Rust implementation for DBSCANSD, a trajectory clustering algorithm.
- lazear/dbscan - Dependency free implementation of DBSCAN clustering in Rust
- whizsid/kddbscan-rs - A rust library inspired by kDDBSCAN clustering algorithm
- Sauro98/appr_dbscan_rust - Program implementing the approximate version of DBSCAN introduced by Gan and Tao
- quietlychris/density_clusters - A naive density-based clustering algorithm written in Rust
- milesgranger/gap_statistic - Dynamically get the suggested clusters in the data for unsupervised learning.
- genbattle/rkm - Generic k-means implementation written in Rust
- selforgmap/som-rust - Self Organizing Map (SOM) is a type of Artificial Neural Network (ANN) that is trained using an unsupervised, competitive learning to produce a low dimensional, discretized representation (feature map) of higher dimensional data.
СТАТИСТИЧЕСКИЕ МОДЕЛИ
- Redpoll/changepoint - Includes the following change point detection algorithms: Bocpd -- Online Bayesian Change Point Detection Reference. BocpdTruncated -- Same as Bocpd but truncated the run-length distribution when those lengths are unlikely.
- krfricke/arima - ARIMA modelling for Rust
- Daingun/automatica - Automatic Control Systems Library
- rbagd/rust-linearkalman - Kalman filtering and smoothing in Rust
- sanity/pair_adjacent_violators - An implementation of the Pair Adjacent Violators algorithm for isotonic regression in Rust
ЭВОЛЮЦИОННЫЕ АЛГОРИТМЫ
- martinus/differential-evolution-rs - Generic Differential Evolution for Rust
- innoave/genevo - Execute genetic algorithm (GA) simulations in a customizable and extensible way.
- Jeffail/spiril - Rust library for genetic algorithms
- sotrh/rust-genetic-algorithm - Example of a genetic algorithm in Rust and Python
- willi-kappler/darwin-rs - darwin-rs, evolutionary algorithms with Rust
ДРУГИЕ ПРОЕКТЫ
- Are we learning yet?, A work-in-progress to catalog the state of machine learning in Rust
- e-tony/best-of-ml-rust, A ranked list of awesome machine learning Rust libraries
- The Best 51 Rust Machine learning Libraries, RustRepo
- rust-unofficial/awesome-rust, A curated list of Rust code and resources
- Top 16 Rust Machine learning Projects, Open-source Rust projects categorized as Machine learning
- 39+ Best Rust Machine learning frameworks, libraries, software and resourcese, ReposHub
БЛОГИ
- About Rust’s Machine Learning Community, Medium, 2016/1/6, Autumn Engineering
- Rust vs Python: Technology And Business Comparison, 2021/3/4, Miłosz Kaczorowski
- I wrote one of the fastest DataFrame libraries, 2021/2/28, Ritchie Vink
- Polars: The fastest DataFrame library you've never heard of 2021/1/19, Analytics Vidhya
- Data Manipulation: Polars vs Rust, 2021/3/13, Xavier Tao
- State of Machine Learning in Rust – Ehsan's Blog, 2019/5/13, Published by Ehsan
- Ritchie Vink, Machine Learning Engineer, writes Polars, one of the fastest DataFrame libraries in Python and Rust, Xomnia, 2021/5/11
- Quickwit: A highly cost-efficient search engine in Rust, 2021/7/13, quickwit, PAUL MASUREL
- Check out Rust in Production, 2021/8/10, Qovery, @serokell
- Why I started Rust instead of stick to Python, 2021/9/26, Medium, Geek Culture, Marshal SHI
ОБУЧЕНИЕ
- Rust Machine Learning Book, Examples of KMeans and DBSCAN with linfa-clustering
- Artificial Intelligence and Machine Learning – Practical Rust Projects(Building Game, Physical Computing) – Dev Guis , 2021/5/19
- Machine learning in Rust using Linfa, LogRocket Blog, 2021/4/30, Timeular, Mario Zupan, Examples of LogisticRegression
- Machine Learning in Rust, Smartcore, Medium, The Startup, 2021/1/15 (c) Vlad Orlov
- Machine Learning in Rust, Logistic Regression, Medium, The Startup, 2021/1/6 (c) Vlad Orlov
- Machine Learning in Rust, Linear Regression, Medium, The Startup, 2020/12/16 (c) Vlad Orlov
- Machine Learning in Rust, 2016/3/7, James, Examples of LogisticRegressor
- Machine Learning and Rust (Part 1): Getting Started!, Level Up Coding, 2021/1/9, Stefano Bosisio
- Machine Learning and Rust (Part 2): Linear Regression, Level Up Coding, 2021/6/15, Stefano Bosisio
- Machine Learning and Rust (Part 3): Smartcore, Dataframe, and Linear Regression, Level Up Coding, 2021/7/1, Stefano Bosisio
- Tensorflow Rust Practical Part 1, Programmer Sought, 2018
- A Machine Learning introduction to ndarray, RustFest 2019, 2019/11/12 (c) Luca Palmieri
- Simple Linear Regression from scratch in Rust, Web Development, Software Architecture, Algorithms and more, 2018/12/13, philipp
- Interactive Rust in a REPL and Jupyter Notebook with EVCXR, Depth-First, 2020/9/21, Richard L. Apodaca
- Rust for Data Science: Tutorial 1, dev, 2021/8/25, Davide Del Papa
- petgraph_review, 2019/10/11, Timothy Hobbs
- Rust for ML. Rust, Medium, Tempus Ex, 2021/8/1, Michael Naquin
- Adventures in Drone Photogrammetry Using Rust and Machine Learning (Image Segmentation with linfa and DBSCAN), 2021/11/14, CHRISTOPHER MORAN
ПРИКЛАДНЫЕ РЕСУРСЫ
- Deep Learning in Rust: baby steps, Medium, 2016/2/2, Theodore DeRego
- A Rust SentencePiece implementation, Rust NLP tales, 2020/5/30
- Accelerating text generation with Rust, Rust NLP tales, 2020/11/21
- A Simple Text Summarizer written in Rust, Towards Data Science, 2020/11/24,Examples of Text Sentence Vector, Cosine Distance and PageRank (c)Charles Chan
- Extracting deep learning image embeddings in Rust, RecoAI, 2021/6/1, Paweł Jankiewic, Examples of ONNX
- Deep Learning in Rust with GPU, 2021/7/30, Xavier Tao
- tch-rs pretrain example - Docker for PyTorch rust bindings tch-rs. Example of pretrain model, 2021/8/15, vaaaaanquish
- Rust ANN search Example - Image search example by approximate nearest-neighbor library In Rust, 2021/8/15, vaaaaanquish
- dzamkov/deep-learning-test - Implementing deep learning in Rust using just a linear algebra library (nalgebra), 2021/8/30, dzamkov
- vaaaaanquish/rust-machine-learning-api-example - The axum example that uses resnet224 to infer images received in base64 and returns the results., 2021/9/7, vaaaaanquish
- Rust for Machine Learning: Benchmarking Performance in One-shot - A Rust implementation of Siamese Neural Networks for One-shot Image Recognition for benchmarking performance and results, UofT Machine Intelligence Student Team
- Why Wallaroo Moved From Pony To Rust, 2021/8/19, Wallaroo.ai
- epwalsh/rust-dl-webserver - Example of serving deep learning models in Rust with batched prediction, 2021/11/16, epwalsh
- Production users - Rust Programming Language, by rust-lang.org
- Taking ML to production with Rust: a 25x speedup, A LEARNING JOURNAL, 2019/12/1 (c) @algo_luca
- 9 Companies That Use Rust in Production, serokell, 2020/11/18, Gints Dreimanis
- Masked Language Model on Wasm, BERT on flontend examples, optim-corp/masked-lm-wasm, 2021/8/27, Optim
- Serving TensorFlow with Actix-Web, kykosic/actix-tensorflow-example
- Serving PyTorch with Actix-Web, kykosic/actix-pytorch-example
ФОРУМЫ
- Natural Language Processing in Rust : rust, 2016/12/6
- Future prospect of Machine Learning in Rust Programming Language : MachineLearning, 2017/11/11
- Interest for NLP in Rust? - The Rust Programming Language Forum, 2018/1/19
- Is Rust good for deep learning and artificial intelligence? - The Rust Programming Language Forum, 2018/11/18
- ndarray vs nalgebra : rust, 2019/5/28
- Taking ML to production with Rust | Hacker News, 2019/12/2
- Who is using Rust for Machine learning in production/research? : rust, 2020/4/5
- Deep Learning in Rust, 2020/8/26
- SmartCore, fast and comprehensive machine learning library for Rust! : rust, 2020/9/29
- Deep Learning in Rust with GPU on ONNX, 2021/7/31
- Rust vs. C++ the main differences between these popular programming languages, 2021/8/25
- I wanted to share my experience of Rust as a deep learning researcher, 2021/9/2
- How far along is the ML ecosystem with Rust?, 2021/9/15
КНИГИ
-- 2019/12/10, Joydeep BhattacharjeeWrite machine learning algorithms in Rust
- Use Rust libraries for different tasks in machine learning
- Create concise Rust packages for your machine learning applications
- Implement NLP and computer vision in Rust
- Deploy your code in the cloud and on bare metal servers
--
-- 2021/9/3, Shahin RostamiPlotting with Plotters and Plotly
- Operations with ndarray
- Descriptive Statistics
- Interactive Diagram
- Visualisation of Co-occurring Types
- download source code and dataset
ВИДЕО УРОКИ
- The /r/playrust Classifier: Real World Rust Data Science, RustConf 2016, 2016/10/05, Suchin Gururangan & Colin O'Brien
- Building AI Units in Rust, FOSSASIA 2018, 2018/3/25, Vigneshwer Dhinakaran
- Python vs Rust for Simulation, EuroPython 2019, 2019/7/10, Alisa Dammer
- Machine Learning is changing - is Rust the right tool for the job?, RustLab 2019, 2019/10/31, Luca Palmieri
- Using TensorFlow in Embedded Rust, 2020/09/29, Ferrous Systems GmbH, Richard Meadows
- Writing the Fastest GBDT Library in Rust, 2021/09/16, RustConf 2021, Isabella Tromba
Подкасты
DATA SCIENCE AT HOME:
- Rust and machine learning #1 (Ep. 107)
- Rust and machine learning #2 with Luca Palmieri (Ep. 108)
- Rust and machine learning #3 with Alec Mocatta (Ep. 109)
- Rust and machine learning #4: practical tools (Ep. 110)
- Machine Learning in Rust: Amadeus with Alec Mocatta (Ep. 127)
- Rust and deep learning with Daniel McKenna (Ep. 135)
- Is Rust flexible enough for a flexible data model? (Ep. 137)
- Pandas vs Rust (Ep. 144)
- Apache Arrow, Ballista and Big Data in Rust with Andy Grove (Ep. 145)
- Polars: the fastest dataframe crate in Rust (Ep. 146)
- Apache Arrow, Ballista and Big Data in Rust with Andy Grove RB (Ep. 160)