Neuronika Alternatives

neuronika reviews and mentions

• This year I tried solving AoC using Rust, here are my impressions coming from Python!
  6 projects | /r/rust | 2 Jan 2023
• Deep Learning in Rust: Burn 0.4.0 released and plans for 2023
  6 projects | /r/rust | 2 Jan 2023

  Also perhaps comparing to Neuronika.

• Making a better Tensorflow thanks to strong typing
  6 projects | /r/rust | 26 May 2022

  how does it compare with https://github.com/spearow/juice, https://github.com/neuronika/neuronika and https://github.com/spearow/juice?

• [D] To what extent can Rust be used for Machine Learning?
  3 projects | /r/MachineLearning | 14 Apr 2022

  Check where and how this struct is used. https://github.com/neuronika/neuronika/blob/variable-rework/neuronika-variable/src/history.rs

• What do I need for an ML/DL based scripting language in Rust?
  1 project | /r/rust | 15 Mar 2022

  Also you can take a look at neuronika.

• ML in Rust
  1 project | /r/rust | 7 Feb 2022

  There is also https://github.com/neuronika/neuronika

• Enzyme: Towards state-of-the-art AutoDiff in Rust
  3 projects | /r/rust | 12 Dec 2021

  I have a question: as the maintainer of [neuronika](https://github.com/neuronika/neuronika), a crate that offers dynamic neural network and auto-differentiation with dynamic graphs, I'm looking at a future possible feature for such framework consisting in the possibility of compiling models, getting thus rid of the "dynamic" part, which is not always needed. This would speed the inference and training times quite a bit.

• Any role that Rust could have in the Data world (Big Data, Data Science, Machine learning, etc.)?
  8 projects | /r/rust | 4 Dec 2021
• What sort of mature, open-source libraries do you feel Rust should have but currently lacks?
  22 projects | /r/rust | 1 Nov 2021

  If you like autograd you will love neuronika

• bhtsne 0.5.0, now 5.6x faster on a 4 core machine, plus a summary of my Rust journey (so far)
  2 projects | /r/rust | 15 Oct 2021

  After reading most of the book, I wanted to get my hands dirty. My initial idea was to build a small machine learning framework but I deemed it to be too difficult if not impossible for me at the time. (Now, neuronika would have something to say). When gathering the bibliography for my thesis, I recalled to have stumbled upon a particular algorithm, t-SNE, whom I liked very much. I found the idea behind it to be very clever and elegant (t-SNE it's still one of my favorite algorithms, together with backprop and SOM, I find manifold learning fascinating in general). "So be it", I said, and I began writing a mess of a code, that was basically a translation of the C++ implementation. Boy was it bad.

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