Rust and machine learning #4: practical tools (Ep. 110)

In this episode I make a non exhaustive list of machine learning tools and frameworks, written in Rust. Not all of them are mature enough for production environments. I believe that community effort can change this very quickly.To make a comparison with the Python ecosystem I will cover frameworks for linear algebra (numpy), dataframes (pandas), off-the-shelf machine learning (scikit-learn), deep learning (tensorflow) and reinforcement learning (openAI).Rust is the language of the future.Happy coding! ReferenceBLAS linear algebra https://en.wikipedia.org/wiki/Basic_Linear_Algebra_SubprogramsRust dataframe https://github.com/nevi-me/rust-dataframeRustlearn https://github.com/maciejkula/rustlearnRusty machine https://github.com/AtheMathmo/rusty-machineTensorflow bindings https://lib.rs/crates/tensorflowJuice (machine learning for hackers) https://lib.rs/crates/juiceRust reinforcement learning https://lib.rs/crates/rsrl This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit datascienceathome.substack.com