https://github.com/georgeguimaraes/awesome-ml-gen-ai-elixir
A curated list of Machine Learning libraries and resources for the Elixir programming language.
https://github.com/georgeguimaraes/awesome-ml-gen-ai-elixir
List: awesome-ml-gen-ai-elixir
ai awesome awesome-list elixir elixir-lang elixir-language elixir-programming-language machine-learning ml
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A curated list of Machine Learning libraries and resources for the Elixir programming language.
- Host: GitHub
- URL: https://github.com/georgeguimaraes/awesome-ml-gen-ai-elixir
- Owner: georgeguimaraes
- License: other
- Created: 2024-01-05T14:22:50.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2025-01-02T18:19:26.000Z (about 2 months ago)
- Last Synced: 2025-01-07T16:00:56.212Z (about 2 months ago)
- Topics: ai, awesome, awesome-list, elixir, elixir-lang, elixir-language, elixir-programming-language, machine-learning, ml
- Homepage:
- Size: 41 KB
- Stars: 90
- Watchers: 1
- Forks: 3
- Open Issues: 0
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Metadata Files:
- Readme: readme.md
- Contributing: contributing.md
- License: license.md
- Code of conduct: code-of-conduct.md
Awesome Lists containing this project
- ultimate-awesome - awesome-ml-gen-ai-elixir - A curated list of Machine Learning libraries and resources for the Elixir programming language. . (Other Lists / Julia Lists)
README
# Awesome ML & GenAI in Elixir
A curated list of Machine Learning (ML) and Generative AI (GenAI) packages and resources for the [Elixir](https://elixir-lang.org/) programming language.
Besides giving an overview for experienced Elixir developers, this list can be useful for ML and AI practitioners looking for other ecosystems.
## Contents
- [Core Tools](#core-tools)
- [Machine Learning](#machine-learning)
- [Traditional Machine Learning](#traditional-machine-learning)
- [Deep Learning](#deep-learning)
- [Generative AI](#generative-ai)
- [Livebooks & Examples](#livebooks--examples)
- [Resources](#resources)
## Core Tools
- [Nx](https://github.com/elixir-nx/nx) - Tensors for Elixir with compilation to CPU/GPU. It is the base for a lot of other libraries.
- [Explorer](https://github.com/elixir-explorer/explorer) - Series and dataframes for data exploration in Elixir.
- [Livebook](https://livebook.dev/) - Write interactive and collaborative notebooks, with integrations to databases, messaging, visualization and more.
- [Kino](https://github.com/livebook-dev/kino) - Render rich and interactive output. Used in Livebook.
## Machine Learning
### Traditional Machine Learning
- [Scholar](https://github.com/elixir-nx/scholar) - Traditional machine learning tools built on top of Nx. Implements algorithms for:
- Classification
- Regression
- Clustering
- Dimensionality reduction
- Metrics and preprocessing
- [EXGBoost](https://github.com/acalejos/exgboost) - Decision Trees implemented using the [XGBoost C API](https://xgboost.readthedocs.io/en/latest/c.html).
- [Mockinjay](https://github.com/acalejos/mockingjay) - Implementation of Microsoft's [Hummingbird](https://github.com/microsoft/hummingbird) library for converting trained Decision Tree models into Nx tensor computations.
- [Soothsayer](https://github.com/georgeguimaraes/soothsayer) - Time series forecasting library inspired by Facebook's Prophet and NeuralProphet.
- [Ulam](https://github.com/tmbb/ulam_ex) - Elixir interface to [Stan](https://mc-stan.org/), a probabilist programming language.
### Deep Learning
- [Axon](https://github.com/elixir-nx/axon) - Neural Networks for Elixir. Built with Nx.
- [Bumblebee](https://github.com/elixir-nx/bumblebee) - Pre-trained neural network models on top of Axon. Provides integration with [Hugging Face](https://huggingface.co/).
- [Ortex](https://github.com/elixir-nx/ortex) - Wrapper around ONNX. Enables you to run ONNX models using Nx.
### Computer Vision
- [Evision](https://github.com/cocoa-xu/evision) - OpenCV bindings for Elixir/Erlang.
- [NxImage](https://github.com/elixir-nx/nx_image) - Image processing in Nx.
## Generative AI
### LLM Tools
- [Honeycomb](https://github.com/seanmor5/honeycomb) - Fast LLM inference built on Elixir, Bumblebee, and EXLA.
- [Instructor.ex](https://github.com/thmsmlr/instructor_ex) - Structured outputs from LLMs using Ecto schemas. Works with OpenAI, llama.cpp and Bumblebee.
### Agent Frameworks
- [Jido](https://github.com/agentjido/jido) - Framework for building autonomous, distributed agent systems using traditional AI and ML approaches.
- [LangChain](https://github.com/brainlid/langchain) - Framework for developing applications powered by language models, with support for OpenAI, Anthropic, Google, and Bumblebee models.
## Livebooks & Examples
- [José Valim's Livebooks](https://github.com/josevalim/livebooks) - Livebooks that José used for talks and Advent of Code.
- [Programming Machine Learning](https://github.com/nickgnd/programming-machine-learning-livebooks) - Livebook notebooks with code examples for the [Programming Machine Learning book by Paolo Perrotta](https://pragprog.com/titles/pplearn/programming-machine-learning/)
- [Machine Learning in Elixir](https://github.com/charlieroth/machine-learning-in-elixir) - Livebooks following along with the book [Machine Learning in Elixir by Sean Moriarity](https://pragprog.com/titles/smelixir/machine-learning-in-elixir/)
- [Asynchronous Processing in Elixir](https://github.com/whatyouhide/guide_async_processing_in_elixir) - Interactive guide using Livebook to asynchronous data processing in Elixir.
## Resources
### Books
- [Machine Learning in Elixir - Learning to Learn with Nx and Axon (by Sean Moriarity)](https://pragprog.com/titles/smelixir/machine-learning-in-elixir/)
- [Genetic Algorithms in Elixir - Solve Problems Using Evolution (by Sean Moriarity)](https://pragprog.com/titles/smgaelixir/genetic-algorithms-in-elixir/)
### Videos
- [(2023) A year in production with Machine Learning on the BEAM](https://www.youtube.com/watch?v=HP86Svk4hzI) (Explorer, Scholar, Bumblebee, Livebook)
- [(2023) Nx-powered decision trees](https://www.youtube.com/watch?v=rbmviKT6HkU) (Nx, EXGBoost)
- [(2023) Building AI apps with Elixir](https://www.youtube.com/watch?v=TfZI5-oQSqI)
- [(2023) MLOps in Elixir: Simplifying traditional MLOps with Elixir](https://www.youtube.com/watch?v=6aVnwj8WQq4) (Nx, Bumbleblee)
- [(2023) Fine-tuning language models with Axon](https://www.youtube.com/watch?v=-iZIZHgHa5M) (Axon)
- [(2023) Data wrangling with Livebook and Explorer](https://www.youtube.com/watch?v=U6nuPjyAUPw) (Livebook, Explorer)
- [(2022) The Future AI Stack by Chris Grainer](https://www.youtube.com/watch?v=Y2Nr4dNu6hI) (Explorer, Axon)
- [(2022) Announcing Bumblebee: pre-trained machine learning models for GPT2, StableDiffusion, and more](https://www.youtube.com/watch?v=g3oyh3g1AtQ) (Livebook, Bumblebee)
- [(2022) Axon: functional programming for deep learning](https://www.youtube.com/watch?v=NWXSiZ-vi-o) (Axon)
### Articles
- (2023) [From Python to Elixir Machine Learning](https://www.thestackcanary.com/from-python-pytorch-to-elixir-nx/) - Nice wrapup on what you gain from the Elixir ecosystem for Machine Learning.
## Contributions
Contributions welcome! Read the [contribution guidelines](contributing.md) first.
## License
This project is licensed under the [CC0 License](LICENSE.md). Feel free to use, share, and adapt the content.