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Multi-type data parallel learning method and device, computer equipment and medium

A learning method and multi-type technology, applied in the direction of neural learning method, biological neural network model, neural architecture, etc., can solve the problem of low efficiency of multi-type cross data processing, and achieve the effect of improving processing speed and accuracy

Pending Publication Date: 2022-01-07
云天弈(广州)智能科技有限公司
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Problems solved by technology

[0003] In view of this, the embodiments of the present disclosure provide a multi-type data parallel learning method, device, computer equipment, and media to solve the problem of multi-type cross data in the prior art due to the characteristics of multiple dimensions and multiple statistical frequencies. Dealing with extremely inefficient problems

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  • Multi-type data parallel learning method and device, computer equipment and medium
  • Multi-type data parallel learning method and device, computer equipment and medium
  • Multi-type data parallel learning method and device, computer equipment and medium

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Embodiment Construction

[0016] In the following description, for the purpose of illustration rather than limitation, specific details such as specific system structures and techniques are presented for a thorough understanding of the embodiments of the present disclosure. It will be apparent, however, to one skilled in the art that the present disclosure may be practiced in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present disclosure with unnecessary detail.

[0017] The present disclosure will be described in detail below with reference to the accompanying drawings and embodiments.

[0018] figure 1 is a schematic diagram of an application scenario of an embodiment of the present disclosure. The application scenario may include a terminal device 1 , a server 2 and a network 3 .

[0019] The terminal device 1 can be hardware or software. W...

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Abstract

The invention relates to the technical field of multi-type data parallel learning, and provides a multi-type data parallel learning method and device, computer equipment and a medium. The method comprises: a splicing module configured to splice intermediate vectors of at least two target sub-neural networks to generate a target vector; a training module that is configured to train the initial neural network by taking the target vector as input to obtain a target neural network; and a calculation module that is configured to import the target data set into the target neural network for calculation to obtain a target predicted value. According to the embodiment, through the steps, the processing speed and accuracy of the multi-type cross data can be greatly improved.

Description

technical field [0001] The present disclosure relates to the technical field of multi-type data parallel learning, and in particular to a multi-type data parallel learning method, device, computer equipment and media. Background technique [0002] With the rapid development of science and technology, the relevant technologies in the field of multi-type data parallel learning technology (especially in the field of machine learning) have made significant progress. However, when dealing with multi-type cross data, due to the characteristics of data with multiple dimensions and multiple statistical frequencies, the processing efficiency of multi-type cross data is extremely low. Contents of the invention [0003] In view of this, the embodiments of the present disclosure provide a multi-type data parallel learning method, device, computer equipment, and media to solve the problem of multi-type cross data in the prior art due to the characteristics of multiple dimensions and mu...

Claims

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Application Information

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IPC IPC(8): G06N3/04G06N3/08
CPCG06N3/08G06N3/045
Inventor 金利杰亢保星
Owner 云天弈(广州)智能科技有限公司
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