arXiv · 2108.09615
Apache Submarine: A Unified Machine Learning Platform Made Simple
Abstract
As machine learning is applied more widely, it is necessary to have a machine learning platform for both infrastructure administrators and users including expert data scientists and citizen data scientists to improve their productivity. However, existing machine learning platforms are ill-equipped to address the "Machine Learning tech debts" such as glue code, reproducibility, and portability. Furthermore, existing platforms only take expert data scientists into consideration, and thus they are inflexible for infrastructure administrators and non-user-friendly for citizen data scientists. We propose Submarine, a unified machine learning platform, to address the challenges.
Explore related subjects
Keep this discovery
Explore connections, maps & timelines
Kai-Hsun Chen, Huan-Ping Su, Wei-Chiu Chuang, Hung-Chang Hsiao, Wangda Tan, Zhankun Tang, Xun Liu, Yanbo Liang, Wen-Chih Lo, Wanqiang Ji, Byron Hsu, Keqiu Hu, HuiYang Jian, Quan Zhou, Chien-Min Wang. 2021-08-22. Apache Submarine: A Unified Machine Learning Platform Made Simple. https://arxiv.org/abs/2108.09615
Cite the original work for its findings. Save a collection to share your selection of sources.