))
An Architect's Guide to Machine Learning Operations and Required Data Infrastructure
Manage episode 438396622 series 3570694
内容由HackerNoon提供。所有播客内容（包括剧集、图形和播客描述）均由 HackerNoon 或其播客平台合作伙伴直接上传和提供。如果您认为有人在未经您许可的情况下使用您的受版权保护的作品，您可以按照此处概述的流程进行操作https://zh.player.fm/legal。
This story was originally published on HackerNoon at: https://hackernoon.com/an-architects-guide-to-machine-learning-operations-and-required-data-infrastructure.
MLOps is a set of practices and tools aimed at addressing the specific needs of engineers building models and moving them into production.
Check more stories related to cloud at: https://hackernoon.com/c/cloud. You can also check exclusive content about #minio, #minio-blog, #mlops, #machine-learning-operations, #machine-learning, #data-engineering, #data-lake, #good-company, and more.
This story was written by: @minio. Learn more about this writer by checking @minio's about page, and for more stories, please visit hackernoon.com.
MLOps is a set of practices and tools aimed at addressing the specific needs of engineers building models and moving them into production. Some organizations start off with a few homegrown tools that version datasets after each experiment and checkpoint models after every epoch of training. Many organizations have chosen to adopt a formal tool that has experiment tracking, collaboration features, model serving capabilities, and even pipeline features.
749集单集
分享
