Method and device for automatically updating deep learning model and storage medium

The invention provides a method and device for automatically updating a deep learning model and a storage medium. The method comprises the following steps: a server deploys a trained initial first deep learning model into a client, collects input data for a user as an actual sample for collection, and uses a second deep learning model to perform machine labeling on the actual sample in the serverto obtain a labeled actual sample; and the server updates the initial first deep learning model by using the first deep learning model obtained by retraining the initial first deep learning model by using the first data set and the labeled actual sample. According to the invention, a plurality of powerful algorithm models are deployed at a back-end server to carry out data acquisition in a real application environment and carry out automatic labeling; and then, the marked data set is used for retraining the relatively simple model of the client and updating the relatively simple model to the front-end equipment, so th