scholar

Traditional machine learning on top of Nx (by elixir-nx)

Scholar Alternatives

Similar projects and alternatives to scholar

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a better scholar alternative or higher similarity.

scholar reviews and mentions

Posts with mentions or reviews of scholar. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-04-14.
  • Data wrangling in Elixir with Explorer, the power of Rust, the elegance of R
    7 projects | news.ycombinator.com | 14 Apr 2023
    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!

  • Scholar: Traditional machine learning for Elixir on top of Nx
    1 project | news.ycombinator.com | 29 Mar 2023
  • Does Elixir have an alternative to Scikit Learn?
    1 project | /r/elixir | 8 Feb 2023
  • Bumblebee: GPT2, Stable Diffusion, and More in Elixir
    5 projects | news.ycombinator.com | 8 Dec 2022
  • XL-ML: Native ML Algorithms for Elixir
    2 projects | /r/elixir | 10 Sep 2022
    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
  • A note from our sponsor - SaaSHub
    www.saashub.com | 26 Apr 2024
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Stats

Basic scholar repo stats
5
342
8.8
5 days ago

elixir-nx/scholar is an open source project licensed under Apache License 2.0 which is an OSI approved license.

The primary programming language of scholar is Elixir.


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