Corgi: Rust neural network/dynamic automatic differentiation library I have been working on

This page summarizes the projects mentioned and recommended in the original post on /r/rust

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  1. corgi

    A neural network, and tensor dynamic automatic differentiation implementation for Rust. (by patricksongzy)

    Fully-connected neural network: https://github.com/patricksongzy/corgi/blob/main/src/dense.rs

  2. InfluxDB

    InfluxDB – Built for High-Performance Time Series Workloads. InfluxDB 3 OSS is now GA. Transform, enrich, and act on time series data directly in the database. Automate critical tasks and eliminate the need to move data externally. Download now.

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  3. L2

    l2 is a fast, Pytorch-style Tensor+Autograd library written in Rust

    this is really cool! i wrote a library a lot like this last year (https://github.com/bilal2vec/L2) and wrote up a very WIP blog post (https://bilal2vec.github.io/blog/rust/2020/08/02/writing-a-machine-learning-library-in-rust.html) about how i made it if y'all are interested ;)

  4. Java-Machine-Learning

    Deep learning library for Java, with fully connected, convolutional, and recurrent layers. Also features many gradient descent optimization algorithms.

    holyyy another '25 :o I only know one other guy who made a autograd library while in hs/first year uni (https://github.com/Daniel-Liu-c0deb0t/Java-Machine-Learning) so it is so cool to see other people doing this!!

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