Jiang, Beibei
781e07249c
Reviewed-by: gtema <artem.goncharov@gmail.com> Co-authored-by: Jiang, Beibei <beibei.jiang@t-systems.com> Co-committed-by: Jiang, Beibei <beibei.jiang@t-systems.com>
2.6 KiB
Data Management
During AI development, massive volumes of data need to be processed, and data preparation and labeling usually take more than half of the development time. ModelArts data management provides an efficient data management and labeling framework. It supports various data types such as image, text, audio, and video in a range of labeling scenarios such as image classification, object detection, speech paragraph labeling, and text classification. ModelArts data management can be used in AI projects of computer vision, natural language processing, and audio and video analysis. In addition, it provides functions such as data filtering, data analysis, team labeling, and version management for full-process data labeling.
Team labeling enables multiple members to label a dataset, improving labeling efficiency. ModelArts allows project-based management for labeling by individual developers, small-scale labeling by small teams, and large-scale labeling by professional teams.
For large-scale team labeling, ModelArts provides team management, personnel management, and data management to implement the entire process, from project creation, allocation, management, labeling, to acceptance. For small-scale labeling by individuals and small teams, ModelArts provides an easy-to-use labeling tool to minimize project management costs.
In addition, the labeling platform ensures data security. User data is used only within the authorized scope. The labeling object allocation policy ensures user data privacy and implements data anonymization.