https://github.com/fl03/concision

Concision is a complete machine-learning toolkit written in pure Rust and optimized for WebAssembly (WASM) operations.
https://github.com/fl03/concision

ai data-science machine-learning math rust scsys toolkit wasm

Last synced: 3 months ago
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Concision is a complete machine-learning toolkit written in pure Rust and optimized for WebAssembly (WASM) operations.

• Host: GitHub
• URL: https://github.com/fl03/concision
• Owner: FL03
• License: apache-2.0
• Created: 2022-10-17T17:23:07.000Z (over 2 years ago)
• Default Branch: main
• Last Pushed: 2024-05-18T20:25:23.000Z (8 months ago)
• Last Synced: 2024-05-19T14:52:33.234Z (8 months ago)
• Topics: ai, data-science, machine-learning, math, rust, scsys, toolkit, wasm
• Language: Rust
• Homepage: https://fl03.github.io/concision/
• Size: 1.09 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 15
• Metadata Files:
  • Readme: README.md
  • Funding: .github/FUNDING.yml
  • License: LICENSE
  • Security: SECURITY.md

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README

        
# Concision

[![crates.io](https://img.shields.io/crates/v/concision.svg)](https://crates.io/crates/concision)

[![docs.rs](https://docs.rs/concision/badge.svg)](https://docs.rs/concision)

[![clippy](https://github.com/FL03/concision/actions/workflows/clippy.yml/badge.svg)](https://github.com/FL03/concision/actions/workflows/clippy.yml)

[![rust](https://github.com/FL03/concision/actions/workflows/rust.yml/badge.svg)](https://github.com/FL03/concision/actions/workflows/rust.yml)

***

### _The library is currently in the early stages of development and is not yet ready for production use._

Concision is designed to be a complete toolkit for building machine learning models in Rust.

Concision is a machine learning library for building powerful models in Rust prioritizing ease-of-use, efficiency, and flexability. The library is built to make use of the 

both the upcoming `autodiff` experimental feature and increased support for generics in the 2024 edition of Rust.

## Getting Started

### Building from the source

Start by cloning the repository

```bash

git clone https://github.com/FL03/concision.git

cd concision

```

```bash

cargo build --features full -r --workspace

```

## Usage

### Example: Linear Model (biased)

```rust

    extern crate concision as cnc;

    use cnc::prelude::{linarr, Linear, Result, Sigmoid};

    use ndarray::Ix2;

    fn main() -> Result<()> {

        tracing_subscriber::fmt::init();

        tracing::info!("Starting linear model example");

        let (samples, d_in, d_out) = (20, 5, 3);

        let data = linarr::((samples, d_in)).unwrap();

        let model = Linear::::from_features(d_in, d_out).uniform();

        // let model = Linear::::from_features(d_in, d_out).uniform();

        assert!(model.is_biased());

        let y = model.activate(&data, Sigmoid::sigmoid).unwrap();

        assert_eq!(y.dim(), (samples, d_out));

        println!("Predictions:\n{:?}", &y);

        Ok(())

    }

```

## Contributing

Pull requests are welcome. For major changes, please open an issue first

to discuss what you would like to change.

Please make sure to update tests as appropriate.

## License

* [Apache-2.0](https://choosealicense.com/licenses/apache-2.0/)

* [MIT](https://choosealicense.com/licenses/mit/)