[D] Looking for open source projects to contribute

This page summarizes the projects mentioned and recommended in the original post on reddit.com/r/MachineLearning

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  • milvus

    Vector database for scalable similarity search and AI applications.

    I am a part of the vector database project Milvus, we welcome open-source contributors to work on Golang (the distributed database) and C++ (ANN algorithm). https://github.com/milvus-io/milvus

  • bootcamp

    Dealing with all unstructured data, such as reverse image search, audio search, molecular search, video analysis, question and answer systems, NLP, etc. (by milvus-io)

    For more beginner tasks associated with the Milvus vector database, you can contribute to the Bootcamp project( https://github.com/milvus-io/bootcamp), where we build a lot of data-driven solutions using ML and Milvus vector database, including reverse image search, recommender systems, etc.

  • Scout APM

    Less time debugging, more time building. Scout APM allows you to find and fix performance issues with no hassle. Now with error monitoring and external services monitoring, Scout is a developer's best friend when it comes to application development.

  • Gorgonia

    Gorgonia is a library that helps facilitate machine learning in Go.

    If you know Go, Gorgonia is a pure Go framework for doing deep learning and various other autograd related things. I'd see it as a bastard baby of PyTorch and TensorFlow. We're always looking for new contributors.

  • nn

    🧑‍🏫 50! Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠

  • Flux.jl

    Relax! Flux is the ML library that doesn't make you tensor

    Hey! I highly suggest checking out: https://fluxml.ai ! There are so many impactful opportunities to contribute. Please ping me if you have any questions.

  • poutyne

    A simplified framework and utilities for PyTorch

    Hi, I'm the author of Poutyne, a library that aims to simplify the use of PyTorch while keeping all its flexibility. Always looking for contributions. If you look in the issue on the Github repo, you'll few suggestions but I'm always looking for other ideas to improve the library.

  • docarray

    The data structure for unstructured data

    hi if you speak Python, checkout https://github.com/jina-ai/docarray it’s a very new project and very easy to contribute

  • JetBrains

    Developer Ecosystem Survey 2022. Take part in the Developer Ecosystem Survey 2022 by JetBrains and get a chance to win a Macbook, a Nvidia graphics card, or other prizes. We’ll create an infographic full of stats, and you’ll get personalized results so you can compare yourself with other developers.

  • habitat-sim

    A flexible, high-performance 3D simulator for Embodied AI research.

    There are plenty of them out there. I spend a lot of time contributing to open source projects like Habitat-Sim https://github.com/facebookresearch/habitat-sim and Habitat-Lab https://github.com/facebookresearch/habitat-lab which have a ton of open issues and code maintaince stuff that we would welcome contributions of.

  • habitat-lab

    A modular high-level library to train embodied AI agents across a variety of tasks, environments, and simulators.

    There are plenty of them out there. I spend a lot of time contributing to open source projects like Habitat-Sim https://github.com/facebookresearch/habitat-sim and Habitat-Lab https://github.com/facebookresearch/habitat-lab which have a ton of open issues and code maintaince stuff that we would welcome contributions of.

  • vosk-api

    Offline speech recognition API for Android, iOS, Raspberry Pi and servers with Python, Java, C# and Node

    Vosk speech recognition toolkit needs help as well. Check our github https://github.com/alphacep/vosk-api. We have a lot of ML tasks and simple programming tasks too

  • kaggle-environments

  • imodels

    Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).

    Our package imodels is expanding our sklearn-compatible set of interpretable models and always looking for new contributors!

  • transformers

    🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.

    HuggingFace's libraries are open source and everyone can contribute with features (and sorting issues). In particular, in the transformers library (https://github.com/huggingface/transformers), new architectures are welcome

  • dataqa

    Labelling platform for text using weak supervision.

    Hey, I am the creator and (only contributor today) of open-source https://github.com/dataqa/dataqa, a Python library to explore and annotate documents. It uses weak supervision, is based on spacy, and has a lot of opportunities to add more deep learning and ML functionality. I can guide you through it :-). This would be a great opportunity to be first and lead contributor of an open-source library (outside the creator).

  • general

    I created a dataset of github projects.

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

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