forked from docs/doc-exports
Lai, Weijian
6aa966a79a
Reviewed-by: Pruthi, Vineet <vineet.pruthi@t-systems.com> Co-authored-by: Lai, Weijian <laiweijian4@huawei.com> Co-committed-by: Lai, Weijian <laiweijian4@huawei.com>
1.8 KiB
1.8 KiB
Processing Data
After data is collected and imported, the data cannot directly meet the training requirements. Process data during R&D to ensure data quality and prevent negative impact on subsequent operations (such as data labeling and model training). ModelArts provides data processing to extract valuable and meaningful data from a large amount of disordered and difficult-to-understand data.
ModelArts provides four basic data processing functions:
- Data validation: helps AI developers identify invalid data, such as damaged data and unqualified data, and effectively prevent algorithm precision deterioration or training failures caused by noisy data.
- Data cleansing: checks data consistency based on data validation and correct some invalid values.
- Data selection: During AI development, a large amount of duplicate data may exist in the collected data. The duplicate data does not improve the model precision. Moreover, it takes a long time to label the data. In this case, use data selection to preprocess data and deduplicate collected data.
- Data augmentation: increases the data volume.
Parent topic: Data Analysis and Preview