scholar VS rustler_precompiled

José from the Livebook team. I don't think I can make a pitch because I have limited Python/R experience to use as reference.

My suggestion is for you to give it a try for a day or two and see what you think. I am pretty sure you will find weak spots and I would be very happy to hear any feedback you may have. You can find my email on my GitHub profile (same username).

In general we have grown a lot since the Numerical Elixir effort started two years ago. Here are the main building blocks:

* Nx (https://github.com/elixir-nx/nx/tree/main/nx#readme): equivalent to Numpy, deeply inspired by JAX. Runs on both CPU and GPU via Google XLA (also used by JAX/Tensorflow) and supports tensor serving out of the box

* Axon (https://github.com/elixir-nx/axon): Nx-powered neural networks

* Bumblebee (https://github.com/elixir-nx/bumblebee): Equivalent to HuggingFace Transformers. We have implemented several models and that's what powers the Machine Learning integration in Livebook (see the announcement for more info: https://news.livebook.dev/announcing-bumblebee-gpt2-stable-d...)

* Explorer (https://github.com/elixir-nx/explorer): Series and DataFrames, as per this thread.

* Scholar (https://github.com/elixir-nx/scholar): Nx-based traditional Machine Learning. This one is the most recent effort of them all. We are treading the same path as scikit-learn but quite early on. However, because we are built on Nx, everything is derivable, GPU-ready, distributable, etc.

Regarding visualization, we have "smart cells" for VegaLite and MapLibre, similar to how we did "Data Transformations" in the video above. They help you get started with your visualizations and you can jump deep into the code if necessary.

I hope this helps!

We have recently started a similar effort on the Scholar package inside the Elixir Nx. Our goal is to fill in the gap of sklearn. For instance, here is a PR for KNN: https://github.com/elixir-nx/scholar/pull/21

It's not a pain because of

https://github.com/philss/rustler_precompiled

The users of your library doesn't have to install anything. The library will seem like any Elixir library when they use it.

I created a elixir (wrapper) library to generate password hashes. Other Elixir libraries use a C NIF to generate password hashes. This libary uses a Rust NIF (using Rustler) and the Rust libraries the generate the different hashes. Additionally this library uses RustlerPrecompiled so you don't need to have a Rust compiler installed to use this library. It supports argon2, scrypt, brypt and pbkdf2.

We use the excellent Rustler Precompiled [1] library now so prebuilt binaries ship with the Elixir package. No Rust toolchain needed. :)

[1] https://github.com/philss/rustler_precompiled