datascience
awesome-production-machine-learning
| datascience | awesome-production-machine-learning | |
|---|---|---|
| 4 | 9 | |
| 4,071 | 16,020 | |
| - | 1.6% | |
| 8.3 | 7.5 | |
| 22 days ago | 4 days ago | |
| Creative Commons Zero v1.0 Universal | MIT License |
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datascience
- Datasciene Libraries for Python
- Datascience Libraries for Python
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Good resources for learning ML with time series in Python? Some links I've found, but looking for canonical resources.
This GitHub repo maintains a good list of resources. Check out the "Time Series" section. https://github.com/r0f1/datascience
- Opinionated List of Data Science Libraries for Python
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?
Mage - 🧙 The modern replacement for Airflow. Mage is an open-source data pipeline tool for transforming and integrating data. https://github.com/mage-ai/mage-ai
shap - A game theoretic approach to explain the output of any machine learning model.
mlnotify - 🔔 No need to keep checking your training - just one import line and you'll know the second it's done.
awesome-jax - JAX - A curated list of resources https://github.com/google/jax
machine-learning-for-software-engineers - A complete daily plan for studying to become a machine learning engineer.
netron - Visualizer for neural network, deep learning and machine learning models
awesome-bigdata - A curated list of awesome big data frameworks, ressources and other awesomeness.
awesome-mlops - :sunglasses: A curated list of awesome MLOps tools
Kats - Kats, a kit to analyze time series data, a lightweight, easy-to-use, generalizable, and extendable framework to perform time series analysis, from understanding the key statistics and characteristics, detecting change points and anomalies, to forecasting future trends.
awesome-ml-for-cybersecurity - :octocat: Machine Learning for Cyber Security
mlreef - The collaboration workspace for Machine Learning
awesome-ocr