Method and device for neural network training based on block chain, and medium

Abstract

The invention discloses a method and a device for neural network training based on a block chain, and a medium. The method comprises: responding to a training request initiated by a target node, and obtaining a neural network model and sample data provided by the target node; selecting available nodes which meet preset conditions in a block chain network; dividing the sample data into data segments, and distributing the neural network model and the data segments to each available node; controlling each available node to train the neural network model according to the data segments, and obtaining result models; combining each result model to generate neural network training results. The method ensures effect of neural network training relatively, and difficulty of realizing neural network training is relatively low. In addition, the invention also provides a neural network training device based on a block chain and a medium, and beneficial effects are as described above.

Description

technical field [0001] The present invention relates to the technical field of blockchain, in particular to a neural network training method, device and medium based on blockchain. Background technique [0002] After being proposed by many scientists more than ten years ago, the neural network quickly faded away, and its research and development encountered huge obstacles. The main reason was that it was limited by the limitation of computing resources and the shortage of data sources, which made it impossible to train the neural network. Provide strong support. In recent years, due to the development of integrated circuits, computer hardware can gradually adapt to the high-intensity calculation of neural network training. In addition, due to the development of sensor technology, the data samples used for neural network training are also gradually enriched. Therefore, neural network training has once again become Current technology trends. [0003] However, in order to ach...

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Problems solved by technology

[0003] However, in order to achieve the effect of "deep learning" after neural network training, it is still difficult to achieve neural network training only with separate computer hardware.

The current proposed neural network training strategy usually adopts the "cloud computing" solution, but "cloud computing" has relatively high requirements for the compatibility between devices, and requires the compatibility of all devices to meet the same standard, so It is difficult to implement neural network training through "cloud computing"

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