Data acquisition method and device for model training, equipment and storage medium

Abstract

The invention provides a data acquisition method and device applied to model training, equipment and a storage medium. The data acquisition method includes: acquiring a data acquisition demand of a user; analyzing the data acquisition requirements to determine keywords of the data suitable for acquisition; and acquiring data with the keyword. Under the condition that the data volume of the user isinsufficient, the data applied to model training can be accurately obtained based on the method, and data support is provided for subsequent data annotation and model training.

Description

technical field [0001] The present invention generally relates to the field of information technology, and more specifically, relates to a data acquisition method, device, device and storage medium applied to model training. Background technique [0002] Machine learning is an inevitable product of the development of artificial intelligence research to a certain stage. It is committed to improving the performance of the system itself by means of calculation and using experience. In computer systems, "experience" usually exists in the form of "data". Through machine learning algorithms, "models" can be generated from data. Model, when faced with a new sample, the model will provide the corresponding judgment, that is, predict the result. It can be seen that data, as the raw material of machine learning, affects the final effect of machine learning. [0003] It can be seen that the model training process is based on sufficient data. For users with insufficient or no data, it...

AI Technical Summary

Problems solved by technology

It can be seen that data, as the raw material of machine learning, affects the final effect of machine learning

[0003] It can be seen that the model training process is based on sufficient data. For users with insufficient or no data, it is difficult to train a model for solving specific problems.

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