awesome-production-machine-learning
Awesome-Federated-Learning
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awesome-production-machine-learning | Awesome-Federated-Learning | |
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9 | - | |
15,947 | 1,848 | |
2.1% | - | |
7.4 | 0.0 | |
8 days ago | over 1 year ago | |
MIT License | - |
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awesome-production-machine-learning
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Exploring Open-Source Alternatives to Landing AI for Robust MLOps
One trove of treasures is the awesome-production-machine-learning repository on GitHub. This curated list provides a multitude of frameworks, libraries, and software designed to facilitate various stages of the ML lifecycle.
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[P] We are building a curated list of open source tooling for data-centric AI workflows, looking for contributions.
There is a cool, gigantic list for MLOps that I can recommend: https://github.com/EthicalML/awesome-production-machine-learning
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How much of a full DS project pipeline can I do for free?
There are a lot of frameworks and specific tools out there that try to make production ML projects viable; from specific like Airflow (orchestrating jobs) and MLflow (experiment tracking) to more complex ones like Kubeflow. You can have a grasp here.
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Sqldiff: SQLite Database Difference Utility
https://github.com/EthicalML/awesome-production-machine-lear...
- [D] What are the best resources to crack M L system design interviews?
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I'm looking for a tool that let's you visualize the models architecture like this. Any idea what it is called?
https://github.com/EthicalML/awesome-production-machine-learning I think you will find most of the tools to visualize the model on this link.
- Awesome production machine learning - curated list of awesome open source libraries that will help you deploy, monitor, version, scale, and secure your production machine learning [free] [website] [@all]
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Crucial differences in MLOps for deep learning
2/ https://github.com/EthicalML/awesome-production-machine-learning
Awesome-Federated-Learning
We haven't tracked posts mentioning Awesome-Federated-Learning yet.
Tracking mentions began in Dec 2020.
What are some alternatives?
shap - A game theoretic approach to explain the output of any machine learning model.
autogluon - Fast and Accurate ML in 3 Lines of Code
awesome-jax - JAX - A curated list of resources https://github.com/google/jax
awesome-federated-learning - resources about federated learning and privacy in machine learning
netron - Visualizer for neural network, deep learning and machine learning models
awesome-mlops - A curated list of references for MLOps
awesome-mlops - :sunglasses: A curated list of awesome MLOps tools
ben-decentralized-chatbot - YC Hackathon 2018 Winner Project. BEN: A decentralized chatbot that uses federated learning.
awesome-ml-for-cybersecurity - :octocat: Machine Learning for Cyber Security
tinyml-papers-and-projects - This is a list of interesting papers and projects about TinyML.
datascience - Curated list of Python resources for data science.
Aweome-Heathcare-Federated-Learning - A curated list of Federated Learning papers/articles and recent advancements.