BotLibre
awesome-production-machine-learning
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| BotLibre | awesome-production-machine-learning | |
|---|---|---|
| 1 | 9 | |
| 561 | 15,947 | |
| 0.2% | 2.1% | |
| 6.6 | 7.4 | |
| about 1 month ago | 8 days ago | |
| Java | ||
| Eclipse Public License 1.0 | MIT License |
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BotLibre
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
What are some alternatives?
learn - Neuro-symbolic interpretation learning (mostly just language-learning, for now)
shap - A game theoretic approach to explain the output of any machine learning model.
refinery - The data scientist's open-source choice to scale, assess and maintain natural language data. Treat training data like a software artifact.
awesome-jax - JAX - A curated list of resources https://github.com/google/jax
DKPro Core - Collection of software components for natural language processing (NLP) based on the Apache UIMA framework.
netron - Visualizer for neural network, deep learning and machine learning models
deodel - A mixed attributes predictive algorithm implemented in Python.
awesome-mlops - :sunglasses: A curated list of awesome MLOps tools
simplenlg - Java API for Natural Language Generation. Originally developed by Ehud Reiter at the University of Aberdeen’s Department of Computing Science and co-founder of Arria NLG. This git repo is the official SimpleNLG version.
awesome-ml-for-cybersecurity - :octocat: Machine Learning for Cyber Security
sematle - NLU service that converts plain English to known and structured data.
datascience - Curated list of Python resources for data science.