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Quickstart

Welcome to the concision quickstart guide! This guide will help you get started with the concision crate, a complete machine learning framework for Rust. It provides a wide range of features for building and training machine learning models, including support for various data types, optimizers, and loss functions.

Note: It is important to note that a primary consideration of the concision framework is ensuring compatibility in two key areas:

  • autodiff: the upcoming feature enabling rust to natively support automatic differentiation.
  • ndarray: The crate is designed around the ndarray crate, which provides a powerful N-dimensional array type for Rust

Getting Started

Prerequisites

To use concision, you need to have the following installed:

  • Rust (version 1.85 or later)

Installation

You can install the rustup toolchain using the following command:

curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh

After installing rustup, you can install the latest stable version of Rust with:

rustup install stable

You can also install the latest nightly version of Rust with:

rustup install nightly

Building from the source

Start by cloning the repository

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

Then, navigate to the concision directory:

cd concision

Using the cargo tool

To build the crate, you can use the cargo tool. The following command will build the crate with all features enabled:

cargo build -r --locked --workspace --features full

To run the tests, you can use the following command:

cargo test -r --locked --workspace --features full