An awesome list of references for MLOps - Machine Learning Operations :pointright: ml-ops.org*
Las características principales de visenger/awesome-mlops son: Awesome List, Machine Learning Operations, MLOps and Production, Community Resources, Awesome Lists.
Las alternativas de código abierto para visenger/awesome-mlops incluyen: benedekrozemberczki/awesome-decision-tree-papers — A collection of research papers on decision, classification and regression trees with implementations. benedekrozemberczki/awesome-monte-carlo-tree-search-papers — A curated list of Monte Carlo tree search papers with implementations. awesomedata/awesome-public-datasets — This project is a community-maintained, open-access directory of high-quality public datasets. It serves as a… ahundt/awesome-robotics — A curated list of awesome links and software libraries that are useful for robots. benedekrozemberczki/awesome-fraud-detection-papers — A curated list of data mining papers about fraud detection. binhnguyennus/awesome-scalability — This project is a curated knowledge repository that aggregates high-quality resources, technical documentation, and…
A collection of research papers on decision, classification and regression trees with implementations.
A curated list of awesome links and software libraries that are useful for robots.
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
A curated list of data mining papers about fraud detection.