|0.1.1||Oct 11, 2020|
|0.1.0||Oct 6, 2019|
|0.0.1||Aug 19, 2019|
#46 in Machine learning
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Tinguely is a machine learning library implemented entirely in Rust. This library is still in early stages of development.
Tinguely uses mathru for its linear algebra calculations and optimization algorithms. There is still lot of room for optimization, but BLAS/LAPACK support is already integrated.
Currently implemented algorithms:
- Linear Regression
- Logistic Regression
The models all provide predict and train methods enforced by the SupervisedLearn and UnsupervisedLearn traits.
Add this to your
Cargo.toml for the native Rust implementation:
[dependencies.tinguely] version = "0.1"
Add the following lines to 'Cargo.toml' if the openblas library should be used:
[dependencies.tinguely] version = "0.1" default-features = false features = "openblas"
One of the following implementations for linear algebra can be activated as a feature:
- native: Native Rust implementation(activated by default)
- openblas: Optimized BLAS library
- netlib: Collection of mathematical software, papers, and databases
- intel-mkl: Intel Math Kernel Library
- accelerate Make large-scale mathematical computations and image calculations, optimized for high performance and low-energy consumption.(macOS only)
Then import the modules and it is ready to be used.
use tinguely as tg;
Any contribution is welcome!