awesome-production-machine-learning
awesome-ocr
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| awesome-production-machine-learning | awesome-ocr | |
|---|---|---|
| 9 | 1 | |
| 15,947 | 781 | |
| 2.1% | - | |
| 7.4 | 4.0 | |
| 8 days ago | 4 months 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-ocr
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HTR/OCR for Handwritten Text?
Other than that, I've found this list of HTR (handwritten text recognition) options: https://github.com/zacharywhitley/awesome-ocr#handwritten. I'll be working my way through that. Do you know any of the options there, and should I focus on or skip them?
What are some alternatives?
shap - A game theoretic approach to explain the output of any machine learning model.
deep-text-recognition-benchmark - Text recognition (optical character recognition) with deep learning methods, ICCV 2019
awesome-jax - JAX - A curated list of resources https://github.com/google/jax
netron - Visualizer for neural network, deep learning and machine learning models
awesome-project-ideas - Curated list of Machine Learning, NLP, Vision, Recommender Systems Project Ideas
awesome-mlops - :sunglasses: A curated list of awesome MLOps tools
awesome-document-understanding - A curated list of resources for Document Understanding (DU) topic
awesome-ml-for-cybersecurity - :octocat: Machine Learning for Cyber Security
Awesome-Out-Of-Distribution-Detection - A professionally curated list of papers, tutorials, books, videos, articles and open-source libraries etc for Out-of-distribution detection, robustness, and generalization
datascience - Curated list of Python resources for data science.