Data Science at Home

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


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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! 

Reference
  1. BLAS linear algebra https://en.wikipedia.org/wiki/Basic_Linear_Algebra_Subprograms
  • Rust dataframe https://github.com/nevi-me/rust-dataframe
  • Rustlearn https://github.com/maciejkula/rustlearn
  • Rusty machine https://github.com/AtheMathmo/rusty-machine
  • Tensorflow bindings https://lib.rs/crates/tensorflow
  • Juice (machine learning for hackers) https://lib.rs/crates/juice
  • Rust reinforcement learning https://lib.rs/crates/rsrl
  • ...more
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    Data Science at HomeBy Francesco Gadaleta

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