rulinalg
Peroxide
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| rulinalg | Peroxide | |
|---|---|---|
| - | 3 | |
| 279 | 443 | |
| - | - | |
| 0.0 | 9.0 | |
| almost 2 years ago | 5 days ago | |
| Rust | Rust | |
| MIT License | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
rulinalg
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Tracking mentions began in Dec 2020.
Peroxide
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Hey Rustaceans! Got a question? Ask here! (39/2022)!
Rust’s standard library is relatively small by design and doesn’t contain any tools for numeric integration. However, you can probably find a crate on crates.io that does what you need. A quick search suggests Peroxide.
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Is rust good for mathematical computing?
peroxide seems really cool, but I haven't had the opportunity to use it much yet.
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Filling up gaps in the ecosystem
peroxide covers some of this area. It could work as a starting point for something in the ML or probabilistic programming domains.
What are some alternatives?
nalgebra - Linear algebra library for Rust.
Math PHP - Powerful modern math library for PHP: Features descriptive statistics and regressions; Continuous and discrete probability distributions; Linear algebra with matrices and vectors, Numerical analysis; special mathematical functions; Algebra
rust-blas - BLAS bindings for Rust
cgmath-rs - A linear algebra and mathematics library for computer graphics.
rust-opencl - OpenCL bindings for Rust.
notecalc3 - NoteCalc is a handy calculator trying to bring the advantages of Soulver to the web.
rust-gmp
are-we-learning-yet - How ready is Rust for Machine Learning?
blas - Wrappers for BLAS (Fortran)
linfa - A Rust machine learning framework.
rust-GSL - A GSL (the GNU Scientific Library) binding for Rust
smartcore - A comprehensive library for machine learning and numerical computing. The library provides a set of tools for linear algebra, numerical computing, optimization, and enables a generic, powerful yet still efficient approach to machine learning.