A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning
The main features of ethicalml/awesome-production-machine-learning are: Awesome List, Applied Machine Learning, Curated Research Lists, MLOps Foundations, Data and Machine Learning, MLOps and Production, Production Machine Learning, Curated Resource Lists.
Open-source alternatives to ethicalml/awesome-production-machine-learning include: eugeneyan/applied-ml — This project is a comprehensive, curated knowledge base designed to support the development and maintenance of… awesomedata/awesome-public-datasets — This project is a community-maintained, open-access directory of high-quality public datasets. It serves as a… kiloreux/awesome-robotics. josephmisiti/awesome-machine-learning — This project is a comprehensive, community-driven directory of machine learning resources, software libraries, and… jphall663/awesome-machine-learning-interpretability — A curated list of awesome responsible machine learning resources. timzhang642/3d-machine-learning — A resource repository for 3D machine learning.
This project is a comprehensive, curated knowledge base designed to support the development and maintenance of production-grade machine learning systems. It serves as a centralized repository of industry-standard technical literature, engineering case studies, and research papers, providing a structured reference for practitioners navigating the complexities of modern data science and machine learning engineering. The resource distinguishes itself through a cross-domain approach that bridges the gap between academic research and practical implementation. By synthesizing proven industry archit
This project is a community-maintained, open-access directory of high-quality public datasets. It serves as a centralized reference point for researchers, developers, and data scientists to locate reliable information sources across a wide spectrum of industries and scientific fields. By providing a structured index, the repository facilitates the discovery of data necessary for exploratory analysis, machine learning model training, and the development of data-intensive applications. The directory distinguishes itself through a lightweight, platform-agnostic approach to resource indexing that
This project is a comprehensive, community-driven directory of machine learning resources, software libraries, and educational materials. It serves as a centralized knowledge base for developers and researchers, organizing tools and frameworks by their primary programming language and technical domain to simplify discovery across the artificial intelligence ecosystem. The collection distinguishes itself by providing a cross-language development index that spans diverse programming environments, including C, C++, Rust, Clojure, and Python. It covers a wide range of specialized capabilities, fr
A curated list of awesome responsible machine learning resources.